241 Data Scientist jobs in South Africa

At impact.com we are passionate about our people, our technology, and are obsessed with customer success. Working together enables us to grow rapidly, win, and serve the largest brands in the world. We use cutting edge technology to solve real-world problems for our clients and continue to pull ahead of the pack as the leading SaaS platform for businesses to automate their partnerships and grow their revenue like never before. We have an entrepreneurial spirit and a culture where ambition and curiosity is rewarded. If you are looking to join a team where your opinion is valued, your contributions are noticed, and enjoy working with fun and talented people from all over the world, then this is the place for you!

impact.com, the world’s leading partnership management platform, is transforming the way businesses manage and optimize all types of partnerships—including traditional rewards affiliates, influencers, commerce content publishers, B2B, and more. The company’s powerful, purpose-built platform makes it easy for businesses to create, manage, and scale an ecosystem of partnerships with the brands and communities that customers trust to make purchases, get information, and entertain themselves at home, at work, or on the go. To learn more about how impact.com’s technology platform and partnerships marketplace is driving revenue growth for global enterprise brands such as Walmart, Uber, Shopify, Lenovo, L’Oreal, and Fanatics, visit .

We are seeking a talented Senior Data Scientist / Data Scientist with a passion for working with generative AI models such as large language models (LLMs) to join our team. You will be with a Senior Data Scientist within a cross-functional squad on developing and fine-tuning AI models to support influencer marketing activities, providing actionable insights and recommendations through data analysis and modeling to enhance brand/partner discovery capabilities, contracting, content creation, and performance analysis. Your work will play a crucial role in enabling brands and partners to achieve their goals faster and better, proving that a data-driven approach, and the synergy of AI and human intelligence can drive exceptional results in the digital connected economy.

• AI Model Development: Design, develop, and fine-tune machine learning models and large language models (LLMs) specifically for targeted applications in digital marketing.
• Data Analysis: Analyze large datasets to extract actionable insights and trends relevant to the partnership landscape.
• Discovery: Develop algorithms for discovering and recommending suitable creators, influencers, and affiliates based on brand requirements, product offerings, and market trends.
• Process Optimization: Create models to streamline the contracting and negotiation process between brands and influencers.
• Content Creation: Assist in generating content ideas and strategies using AI-driven insights to enhance engagement and reach.
• Performance Analysis: Build predictive models to evaluate the success of marketing campaigns and provide recommendations for improvement.
• Collaboration: Work closely with product managers, marketers, and engineering teams to integrate AI solutions into the platform.
• Research and Innovation: Stay up-to-date with the latest advancements in AI and machine learning, and continuously explore new techniques and technologies to enhance our product offerings.

• Educational Background: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
• Technical Expertise:
• Working knowledge of Python
• Experience with machine learning frameworks/libraries such as TensorFlow, PyTorch, Apache MLlib, or Scikit-learn.
• Well-developed knowledge of machine learning generally, and deep learning specifically.
• Experience with the use of natural language processing (NLP) techniques for textual analysis.
• Experience with data visualization tools (e.g., Tableau, Power BI, Looker).
• Familiarity with SQL
• Knowledge with Big Data processing tech (e.g., BigQuery, Databricks, Spark, Snowflake, Redshift, Hadoop) will be an added advantage.
• Analytical Skills: Problem-solving abilities and exposure to modeling and analyzing large datasets to extract meaningful insights and inform decisions.
• Communication: Excellent written and verbal communication skills, with the ability to present complex technical concepts to non-technical audiences.
• Team Player: Ability to work collaboratively in a cross-functional team environment.
• Adaptability: Willingness to learn new skills and technologies, and to adapt to the evolving needs of the business.
• Experience: At least 2 - 4 years in data-related individual contributor roles.
• Previous experience in a startup or fast-paced environment is desirable.

• Affiliate & Partnerships Industry Fundamentals Certification by PXA

• Unlimited PTO policy
• Take the time off that you need. We are truly committed to a positive work-life balance, recognizing that it is important to be happy and fulfilled in both.
• Training & Development
• Learning the advanced partnership automation products.
• Medical Aid and Provident Fund
• Group schemes with Discovery & Bonitas for medical aid.
• Group scheme with Momentum for provident fund.
• Stock Options
• 3-year vesting schedule pending Board approval.
• Primary caregiver leave
• Internet Allowance
• Flexible work hours
• Casual work environment
• Technology stipend

impact.com is proud to be an equal opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors.

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Job Description

To plan, build, optimise and implement innovative quantitative analytical methodologies, procedures, products and advanced

Job Description

To plan, build, optimise and implement innovative quantitative analytical methodologies, procedures, products and advanced

mathematical models that provide analytical support and interpret insights, using advanced analytics technologies, to address business opportunities and problems and implement business strategy.

Hello, Future Data Scientist III

Welcome to FNB, the home of the #changeables. We design for the shapeshifters and deliver products and services that make us incredibly proud of people that make it happen.

As part of our pricing team, you will be surrounded by unique talents, diverse minds, and an adaptable environment that lives up to the promise of staying curious. Now’s the time to imagine your potential in a team where experts come together and ignite effective change.

To plan, build, optimise and implement innovative quantitative analytical methodologies, procedures, products and advanced mathematical models that provide analytical support and interpret insights, using advanced analytics technologies, to address pricing and business opportunities and problems and implement business strategy.

Are You Someone Who Can

• Innovate by finding the best fit solution for the situation such as the flexibility of delivery and customized pricing and profitability solutions which result in more efficient outcomes.
• Provide input into localisation of appropriate model building policies, standards, frameworks, and governance process and integration of business modelling and analytics value chain.
• Adhere to model building policies, standards, frameworks, and governance process.
• Ensure own ethical usage of information that complies to restrictions applied for privacy and sensitivity classification.
• Understand and ensure implementation and adherence to Privacy business requirements, legislation and policy.
• Ensure reporting of any Information Privacy Incidents and escalate appropriately for resolution of Privacy and Protection Audit Findings, Complaints, Incidents, Investigations and Privacy and Protection Assessments.
• Create delivery plans for achievement of outputs / deliverables in collaboration with business stakeholders to understand information requirements for strategy delivery and define metrics that track performance.
• Analyse available data to identify information commercialisation opportunities that have not been explored to address business needs and revenue options.
• Productionize analytics in the approved FirstRand architecture by translating technical data information into practical business information that addresses identified needs.
• Analyse information requirements, availability and quality of data to feed into management for resolution.
• Contribute to the development of core analytical capabilities or model libraries using advanced statistical, quantitative or econometric techniques and utilise as appropriate.
• Collaborate with numerous departments across the business to aid them in the proper use of data to ensure delivery of desired operational results.
• Participate in relevant project related to the business overall analytical needs and opportunities.
• Serve as SME for retail credit pricing; applying own understanding of the operations of the business product or service.
• Build models that analyse processes to recommend areas for optimisation to achieve cost savings, revenue generation or efficiency improvements for the business.
• Document and audit relevant processes.
• Document and implement models to address specific business requirements.
• Conduct appropriate manipulation and analysis of data to pro-actively identify and meet needs of the business for the purpose of future work and to ensure high information-quality and reliability across the business.
• Apply own understanding of statistical techniques to determine approach to provide input required for decisions and design or evaluation of experiments.
• Apply technical concepts such as (Multivariable Calculus, Linear Algebra etc.) concepts to improve predictive performance or algorithm optimisation in data defined products.
• Implement Machine learning mathematical algorithms and automation techniques using open-source programming languages such as SAS or Python libraries.
• Utilise advanced Predictive modelling techniques to hold insight into outcomes and future events that inform key assumptions.
• Utilise data to model complex abstractions in machine learning research to enable deep learning.
• Utilise pattern recognition technology to recognizes patterns in data and the criteria for use interchangeably with machine learning technology.
• Build and program own statistical model in statistical software for application development to productionize the model into a software application conducted by software developers.
• Conduct Text analytics to examine unstructured data to glean key business insights.
• Understand principles of Data Wrangling to identify and recommend corrective actions for imperfections in data quality.
• Participate in enterprise-wide high level problem resolution by interacting with relevant engineers and product managers, utilising appropriate methods and decide when approximations make sense.
• Conduct data visualisation to present data, findings and techniques to audiences, both technical and nontechnical in a pictorial or graphical format so it can be easily analysed utilising principles of visually encoding data and communicating information.
• Maintain ownership of models through regular audits and updates to ensure relevance.
• Plan and perform regular model updates that capture evolving business complexity in current models.
• Challenge current models to ensure relevance and accuracy of outputs.
• Test outputs and accuracy of models to ensure relevance.
• Use data and analytic insights to provide input into improving customer experience through a better understanding of the customers context to identify monetization opportunities and monitoring implementation of business decisions to recommend enhancements utilizing statistical modelling and data analysis.
• Validate, interpret and create reports and presentations for data analytics management and relevant stakeholders.
• Review and assist more junior Quantitative Analysts with processes and models.
• Participate and contribute to a development culture where information regarding successes, issues, trends and ideas are actively shared.
• Build and sustain collaborative working relationships with relevant peers and stakeholders to achieve productivity synergies.
• Participate in specialist communities of practice and contribute positively to own and organisational knowledge improvement.
• Contribute to the development of a budget aligned to operational delivery plans, monitor effectiveness and report on variances.
• Build relationships that allow for the managing of expectations; the sharing of knowledge and diverse insights; and the creation of buy-in.
• Engage in cross-functional relationships to obtain and to provide work support.
• Take all necessary actions to ensure compliance with relevant statutory, legislative, policy and governance requirements in area of accountability.
• Ensure implementation of relevant policies, governance and practice standards across the business.
• Maintain expert knowledge on relevant legislative amendments, industry best practices and business's internal compliance procedures and requirements.
• Ensure compliance is adopted in terms of systems and procedures as laid out by business.
• Implement and provide input into the development of governance and compliance procedures and processes within area of specialization and identify risks.
• Determine the business questions that need be answered and determine appropriate analytics models for utilization.
• Source and prepare relevant data sources for analysis.
• Translate business requirements into tangible models utilizing own understanding of the business value of projects, models and processes.
• Develop and apply analytical algorithms and methods to build, test and implement advanced mathematical models and analytical solutions that address business problem, opportunities and improve business outcomes i.e. reduced risk and costs, increased profitability, optimized efficiency and to facilitate strategic decision-making.
  
  

• Minimum Qualification - B Degree Maths, Stats, Engineering, Computer Science, Econometrics, Commerce, Physics or Actuarial Science
• Preferred Qualification - Post grad in Maths, Stats, Engineering, Computer Science, Econometrics, Commerce, Physics or Actuarial Science
• Experience – 2/4 years’ experience in a similar environment
  
  

• Opportunities to network and collaborate.
• Challenging work environment.
• Opportunities to innovate.
  
  

• Curious & courageous - you're driven by always wanting to know more and learn more and you're brave enough.
• Obsessed with mastery - you know what it takes to become good at what you do and are constantly pushing yourself to do it.
  
  

• Seniority level Mid-Senior level

• Employment type Full-time

• Job function Engineering and Information Technology
• Industries Banking

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Are you a Data Scientist based in the Eastern Cape or willing to relocate, seeking a new and challenging opportunity? This may be the position you have been searching for!

Requirements :

• Proven track record of at least 5 years applied data science / machine learning
• Experience in leading agile product teams to achieve outstanding data solutions
• Implementation experience for data technology and automation of the data science work flow
• Must have worked on Python / R / Java with machine learning algorithms such neural nets and SVMs
• Experience in MS Azure Data Lake, Databricks and Synapse and Analysis Services
• Experience in MS Power BI, SQL Analysis Services, SQL Database Development

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Direct message the job poster from Frontline Research Group

FUNCTIONAL DESCRIPTION:

We are seeking a highly skilled and analytical Data Scientist to join our market research team. The Data Scientist needs practical knowledge and comprehensive understanding of research processes and techniques. The successful individual will actively assist in the data production process and when required, within the departments. The ideal candidate will be responsible for designing of the sample and survey, sample implementation instructions into field, monthly production and extrapolations to final client delivery, developing innovate models, and generating actionable insights. This role requires a strong foundation in statistics, machine learning, and data visualization, combined with an understanding of market behaviour and dynamics.

As a Data Scientist in the market research domain, you will bridge the gap between raw data and business decision-making, helping stakeholders understand market trends. While mining, interpreting, and reviewing the data, this person will be relied on to ask questions, connect the dots, and uncover hidden opportunities for realising the data’s full potential. As part of a team of specialists, the Data Scientist will “slice and dice” data using various methods and create new visions for the future.

RESPONSIBILITIES:

·Gather and process volumes of structured and unstructured data to identify trends and patterns

·Ensure data integrity, consistency, and accuracy through the use of statistical techniques to validate data for uniformity and accuracy

·Set up and perform additional data reviewing methods using statistics to design more efficient data review processes

·Design samples methodologies and universe for new projects during project setup phases

·Evaluate universe and sample designs for existing projects and implement changes where necessary

·Apply weighting techniques to survey data to ensure representativeness

·Support survey design using statistical principles to ensure validity and reliability

·Design a streamlined restatement process to avoid data step changes

·Work closely with all stakeholders to identify project health issues to develop effective solutions

·Manage and implement data rework /restatements processes for all tracking project projects

·Find innovative solutions to Universe challenges by applying a modelling approach

·Work closely with different teams to apply data-driven insights and provide guidance to the correct use of reported data

·Assist with complex data investigations and analysis

·Serve as a data strategist to identify and integrate existing and new datasets that can be leveraged to enhance our product capabilities, and work closely with the engineering team in the development of data products

·Stay updated with the latest tools, AI technologies and methods in Data Science

·Advise on innovative data collection strategies and recommend best suited approaches.

REQUIREMENTS:

·7+ years of experience in Data Science

·Bachelor’s degree (or equivalent) in Statistics, Applied Mathematics, or related field

• Experience with Excel, PowerPoint, PowerBI, SQL, and statistical tools SPSS, SAS
• Proficiency with data mining, mathematics, and statistical analysis
• Extensive experience in pattern recognition and modelling

We are looking for someone with:

• Eagerness to grow and learn with the company as part of a high-performing team
• Strong numeracy skills and exceptional attention to detail
• A proactive problem solver and quick thinker

·Ability to work effectively in a dynamic, research-oriented group

·Meticulous attention to detail

·Ability to manage competing priorities under demanding deadlines

If you feel that you would be a good fit for the team based on the job role and requirements as specified above, we would love to hear from you! Please submit a detailed CV and cover letter to Human Resources: ( ) by no later than Monday, 4 August 2025.

All appointments will be made in line with Frontline’s EE Strategy.

• Seniority level Mid-Senior level

• Employment type Full-time

• Job function Engineering and Information Technology
• Industries Market Research

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Port Elizabeth, Eastern Cape, South Africa ZAR780,000.00-ZAR1,000,000.00 2 weeks ago

Port Elizabeth, Eastern Cape, South Africa 3 weeks ago

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Port Elizabeth, Eastern Cape, South Africa 2 weeks ago

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Job title : Data Scientist

Job Location : Gauteng, Johannesburg Deadline : August 31, 2025 Quick Recommended Links

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• Job by industries

StartFragment

Job Description

Purpose :

Key Responsibilities :

Model Development & Analytics :

Data Management & Governance :

Business Collaboration & Strategy :

Technical Execution :

Compliance & Governance :

Mentorship & Knowledge Sharing :

Experience Required

End Date : July 29, 2025

EndFragment

Dynamics of the Role:

TransUnion is committed to finding innovative ways information can be used to help businesses and consumers make smarter decisions.

As a data scientist in our team, you’ll join a world class group of data scientists, statisticians and

mathematicians on a mission to derive insights from data and put them to good use. You’ll be responsible for developing credit risk, fraud and customer solutions through consulting engagements and research serving TransUnion’s clients across Financial Services, Telecommunications and Insurance Industries.

How you will contribute:

• You’ll collaborate with cross-functional teams and external partners both locally and internationally to drive the design and development of analytical products and solutions at TU Africa.
• You’ll provide guidance and contribute subject matter expertise in projects involving descriptive, predictive, and prescriptive analysis – leveraging a variety of advanced tools and techniques.
• You’ll deliver analytic insights and recommendations in succinct and compelling presentations for internal and external customers and an executive audience.
• You’ll foster a high-performance culture and cultivate an environment that promotes excellence and reflects the TransUnion brand.

What you will bring to the role:

Education:

• Bachelor’s degree in Statistics, Applied Mathematics, Computer Science, Engineering, or another highly quantitative field (Honors preferred).

Experience:

• 5-8 years of professional experience with analytics and client solutioning projects.
• Multiple examples of demonstrated success in internal and external client-facing analytical roles over a period of at least three (3) years.
• Experience in developing, interpreting and presenting credit risk and propensity models to internal and external clients.
• Strong written and verbal communication skills: ability to clearly articulate ideas to both technical and non-technical audiences, strong presentation skills with comfort presenting to multiple levels within the organisation.
• Strong analytical, critical thinking, and creative problem-solving skills.
• Must be comfortable with presenting generated insights and recommendations to clients.
• Mastery of a statistical programming languages such as R, and SQL; proficiency with Microsoft Office tools.
• Operates with little supervision in a complex, dynamic, matrixed environment. Able to handle multiple tasks at one time.
• Strong project management skills with the ability to manage multiple assignments effectively.
• An understanding of current industry challenges and trends at the level needed to proactively identify customers’ analytical needs and related business opportunities.
• Experience and familiarity with analytical consulting.
• Experience working with credit bureau data and solutions preferred.
• Experience with cloud service platform would be advantageous.

What we offer:

• A work environment that encourages collaboration and innovation at a global scale. We consistently explore new technologies and tools to remain on the forefront of analytical innovation.
• Best in class analytical platforms with proprietary TU analytical tools, shared services and a hybrid-cloud infrastructure
• Our culture encourages our people to hone current skills and build new capabilities, while discovering their genius.

Who we are:

A global leader in credit information and information management services, TransUnion gives businesses, consumers and the global community the power to achieve their goals. Businesses count on us to better manage risk and customer relationships. Consumers are able to better manage credit to achieve their financial goals. And in communities around the world, we help build strong economies and give people the power to achieve their dreams.

Exceptional opportunities are coming as we build on this strong foundation. Our ambitious growth strategy includes substantial new investment worldwide, a wide range of new solutions to help our clients succeed like never before, and new ideas for expanding our reach in every part of our dynamic and fastmoving industry. We’re on an exciting journey and you can be a part of it. We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.

Cape Town/Johannesburg Posted 3 months ago Posted on Data Science

Founded in South Africa in 2007, our client is a globally recognised organisation who build mobile technologies to improve the well-being of people in low and middle-income countries. Working with governments, international NGOs, foundations and social enterprises to create and deliver essential information and vital services.

Since then they have;

● Established the largest maternal mHealth programme

● Run the world’s largest COVID awareness whatsapp chatbot

● Had projects which span topics such as HIV and TB management, global smoking cessation, diabetes and gender based violence (GBV).

● Have expanded to support health workers in managing the health burden,focused on utilising the wide presence of mobile devices even in low income demographics.

Job Overview
As part of our Data Science team, you will work closely with cross-functional teams, including DataOps Engineering, to extract meaningful insights from large and complex datasets, develop visualizations to communicate these insights, provide data-driven recommendations to measure impact and improve services, and contribute to new machine learning and AI initiatives. Analyses and tools developed will be tied to measurable organizational outcomes and impact on health and policy challenges, including those faced by South Africa and the Global South. The suitable candidate would ideally have an interest in developing (or continuing to develop) expertise in combining digital technologies with evidence-based large-scale behaviour change.

Key Focus Areas
● Advanced analytics
○ Use SQL to enable and action dashboard development and ad-hoc reporting requests.
○ Use Python, Machine Learning, and AI to extract other insights or to build new chatbot features.
○ Review chatbots to ensure data gets captured as needed.
○ Use Tableau and Looker Studio to develop dashboards.
○ Collaborate with DataOps Engineering on automating recurring analysis and reporting workflows to improve efficiency.

○ Develop predictive and prescriptive analytics models to forecast health or behavioral outcomes.
○ Apply a range of Machine Learning and AI techniques, including supervised, unsupervised, and reinforcement learning, while optimizing workflows with a focus on key performance metrics like accuracy, precision, and recall.

○ Experiment with, implement and evaluate generative AI methodologies, such as Large Language Models (LLMs), transformers, and RAG techniques.

● Cross-disciplinary collaboration
○ Bridge the gap between Data Science and other teams to maximize the utility of our diverse skill sets.
○ Engage with internal stakeholders, such as funders or research partners, to align insights with strategic goals.
○ Work closely with DataOps Engineering to align data pipelines, MLOps infrastructure, and ETL processes with data science workflows.

● Team growth and self-growth
○ Play an active role in contributing to, and improving, the Data Science team's ways of work, and roadmap for the future.
○ Keep up to date with emerging technologies in the Data Science, Machine Learning, and AI space.

● Communication
○ Effectively communicate complex technical findings to non-technical stakeholders.
○ Communicate and collaborate with external partners when required.
○ Foster a data-driven culture by organizing regular knowledge-sharing sessions or workshops.
○ Facilitate cross-functional problem-solving sessions to align Data Science objectives with organizational needs.

● Ethical considerations:
○ Integrate ethical considerations into data science practices, ensuring responsible and unbiased use of secure data.
○ Proactively address fairness, bias mitigation, and explainability in models deployed in sensitive domains like healthcare.

● Agile methodology
○ Embrace and contribute to an agile work environment, adapting quickly to changing priorities and requirements.

Responsibilities and Duties
● Evaluate new technologies for Data Science, Machine Learning, and AI.
● Actively assist with driving the Data Science strategy within the organisation.
● Provide evidence-based recommendations to inform the strategic implementation of programmes.
● Help us understand if our projects are achieving their goals by measuring and analysing their impact.
● Drive the collection of new data and the refinement of existing data sources.

● Collaborate on implementing best practices for MLOps, including CI/CD pipelines, model monitoring, and scaling production systems, in conjunction with DataOps Engineering.
● Collaborate with DataOps Engineering on building automated impact measurement frameworks, such as A/B testing or causal inference designs.
● Cross-Disciplinary interfacing: The team is drawn from many different backgrounds. A focus area is understanding and extracting the value from these diverse skill sets and ensuring good collaboration with the Data Science team.
● Work collaboratively within the multidisciplinary teams implementing our programmes.
● Work closely with the Monitoring and Evaluation, Strategy and Experience Design, Engineering and SRE teams to design and develop monitoring tools for impact measurement.
● Define and maintain key performance indicators (KPIs) to track the success of data initiatives.

Qualifications
● A degree in Computer Science or a related field. A Master’s Degree in a related technical field (Data Science, Statistics, Math, Software Engineering, Computer Science) is preferred but not required.
● Mathematical training to graduate level (i.e., undergraduate degree in a quantitative subject).

Skills and Experience Required
● 3+ years experience working as a Data Scientist or in a similar role, with a strong focus on data analysis, data visualization, and Machine Learning and AI concepts.
● Proficient in programming languages such as Python, with a deep understanding of the principles of object-oriented programming.
● 3+ years of experience developing dashboards on Tableau, PowerBI, or similar.
● 3+ years experience with SQL.
● Strong experience with cloud platforms such as AWS, Azure, or GCP, and expertise in utilizing cloud-based data services (e.g., AWS Athena, AWS Redshift, Google BigQuery).
● Solid understanding of data modelling.
● Experience using version control systems (e.g., Git).
● Experience in delivering Data Science, Machine Learning, and AI projects to production environments using an agile and responsive approach.
● Ability to visually describe insights and data effectively using dashboarding tools like Tableau or Looker Studio.

● Familiarity with Figma for wireframing and design collaboration will be beneficial but not required.
● Familiarity with data governance, data security, and data privacy practices.
● Excellent problem-solving and research skills and the ability to troubleshoot complex data-related issues.
● Strong communication and collaboration skills to work effectively with cross-functional teams and stakeholders.
● Proven ability to work in a fast-paced environment, handle multiple priorities, and deliver high-quality results within deadlines.
● Experience solving difficult problems with poorly defined constraints.

● Proven ability to understand, prepare, and analyze large and complex data sets. Ability to collaborate and work with cross-functional, multi-disciplinary teams.
● Analyze data, draw insights, and prepare reports in a cohesive, intuitive manner.
● The ability to think strategically, act quickly, multi-task and work collaboratively in an environment that values creativity and flexibility.
● Coaching and mentoring.
● Experience with API development for exposing ML and AI models (e.g., FastAPI).
● Desirable: experience working with remote teams.
● Interest or experience with behaviour change theories.
● Experience in the full Data Science development lifecycle.
● Experience working with sensitive, healthcare-related data.

Job Information Status: Open Job type: Full Time Salary: Negotiable Publish date: 16 Apr 2025 Expire in: 1 month

Cape Town/Johannesburg Posted 3 months ago Posted on Data Science

Founded in South Africa in 2007, our client is a globally recognised organisation who build mobile technologies to improve the well-being of people in low and middle-income countries. Working with governments, international NGOs, foundations and social enterprises to create and deliver essential information and vital services.

Since then they have;

● Established the largest maternal mHealth programme

● Run the world’s largest COVID awareness whatsapp chatbot

● Had projects which span topics such as HIV and TB management, global smoking cessation, diabetes and gender based violence (GBV).

● Have expanded to support health workers in managing the health burden,focused on utilising the wide presence of mobile devices even in low income demographics.

Job Overview
As part of our Data Science team, you will work closely with cross-functional teams, including DataOps Engineering, to extract meaningful insights from large and complex datasets, develop visualizations to communicate these insights, provide data-driven recommendations to measure impact and improve services, and contribute to new machine learning and AI initiatives. Analyses and tools developed will be tied to measurable organizational outcomes and impact on health and policy challenges, including those faced by South Africa and the Global South. The suitable candidate would ideally have an interest in developing (or continuing to develop) expertise in combining digital technologies with evidence-based large-scale behaviour change.

Key Focus Areas
● Advanced analytics
○ Use SQL to enable and action dashboard development and ad-hoc reporting requests.
○ Use Python, Machine Learning, and AI to extract other insights or to build new chatbot features.
○ Review chatbots to ensure data gets captured as needed.
○ Use Tableau and Looker Studio to develop dashboards.
○ Collaborate with DataOps Engineering on automating recurring analysis and reporting workflows to improve efficiency.

○ Develop predictive and prescriptive analytics models to forecast health or behavioral outcomes.
○ Apply a range of Machine Learning and AI techniques, including supervised, unsupervised, and reinforcement learning, while optimizing workflows with a focus on key performance metrics like accuracy, precision, and recall.

○ Experiment with, implement and evaluate generative AI methodologies, such as Large Language Models (LLMs), transformers, and RAG techniques.

● Cross-disciplinary collaboration
○ Bridge the gap between Data Science and other teams to maximize the utility of our diverse skill sets.
○ Engage with internal stakeholders, such as funders or research partners, to align insights with strategic goals.
○ Work closely with DataOps Engineering to align data pipelines, MLOps infrastructure, and ETL processes with data science workflows.

● Team growth and self-growth
○ Play an active role in contributing to, and improving, the Data Science team's ways of work, and roadmap for the future.
○ Keep up to date with emerging technologies in the Data Science, Machine Learning, and AI space.

● Communication
○ Effectively communicate complex technical findings to non-technical stakeholders.
○ Communicate and collaborate with external partners when required.
○ Foster a data-driven culture by organizing regular knowledge-sharing sessions or workshops.
○ Facilitate cross-functional problem-solving sessions to align Data Science objectives with organizational needs.

● Ethical considerations:
○ Integrate ethical considerations into data science practices, ensuring responsible and unbiased use of secure data.
○ Proactively address fairness, bias mitigation, and explainability in models deployed in sensitive domains like healthcare.

● Agile methodology
○ Embrace and contribute to an agile work environment, adapting quickly to changing priorities and requirements.

Responsibilities and Duties
● Evaluate new technologies for Data Science, Machine Learning, and AI.
● Actively assist with driving the Data Science strategy within the organisation.
● Provide evidence-based recommendations to inform the strategic implementation of programmes.
● Help us understand if our projects are achieving their goals by measuring and analysing their impact.
● Drive the collection of new data and the refinement of existing data sources.

● Collaborate on implementing best practices for MLOps, including CI/CD pipelines, model monitoring, and scaling production systems, in conjunction with DataOps Engineering.
● Collaborate with DataOps Engineering on building automated impact measurement frameworks, such as A/B testing or causal inference designs.
● Cross-Disciplinary interfacing: The team is drawn from many different backgrounds. A focus area is understanding and extracting the value from these diverse skill sets and ensuring good collaboration with the Data Science team.
● Work collaboratively within the multidisciplinary teams implementing our programmes.
● Work closely with the Monitoring and Evaluation, Strategy and Experience Design, Engineering and SRE teams to design and develop monitoring tools for impact measurement.
● Define and maintain key performance indicators (KPIs) to track the success of data initiatives.

Qualifications
● A degree in Computer Science or a related field. A Master’s Degree in a related technical field (Data Science, Statistics, Math, Software Engineering, Computer Science) is preferred but not required.
● Mathematical training to graduate level (i.e., undergraduate degree in a quantitative subject).

Skills and Experience Required
● 3+ years experience working as a Data Scientist or in a similar role, with a strong focus on data analysis, data visualization, and Machine Learning and AI concepts.
● Proficient in programming languages such as Python, with a deep understanding of the principles of object-oriented programming.
● 3+ years of experience developing dashboards on Tableau, PowerBI, or similar.
● 3+ years experience with SQL.
● Strong experience with cloud platforms such as AWS, Azure, or GCP, and expertise in utilizing cloud-based data services (e.g., AWS Athena, AWS Redshift, Google BigQuery).
● Solid understanding of data modelling.
● Experience using version control systems (e.g., Git).
● Experience in delivering Data Science, Machine Learning, and AI projects to production environments using an agile and responsive approach.
● Ability to visually describe insights and data effectively using dashboarding tools like Tableau or Looker Studio.

● Familiarity with Figma for wireframing and design collaboration will be beneficial but not required.
● Familiarity with data governance, data security, and data privacy practices.
● Excellent problem-solving and research skills and the ability to troubleshoot complex data-related issues.
● Strong communication and collaboration skills to work effectively with cross-functional teams and stakeholders.
● Proven ability to work in a fast-paced environment, handle multiple priorities, and deliver high-quality results within deadlines.
● Experience solving difficult problems with poorly defined constraints.

● Proven ability to understand, prepare, and analyze large and complex data sets. Ability to collaborate and work with cross-functional, multi-disciplinary teams.
● Analyze data, draw insights, and prepare reports in a cohesive, intuitive manner.
● The ability to think strategically, act quickly, multi-task and work collaboratively in an environment that values creativity and flexibility.
● Coaching and mentoring.
● Experience with API development for exposing ML and AI models (e.g., FastAPI).
● Desirable: experience working with remote teams.
● Interest or experience with behaviour change theories.
● Experience in the full Data Science development lifecycle.
● Experience working with sensitive, healthcare-related data.

Job Information Status: Open Job type: Full Time Salary: Negotiable Publish date: 16 Apr 2025 Expire in: 1 month

Why Entersekt

Founded over 16 years ago, with more recent investments from Accel-KKR, Entersekt is a leader in digital banking fraud prevention and payment security, including mobile authentication, mobile app security, and 3-D Secure authentication for issuers, acquirers and payment networks. We offer highly scalable products with a track record of success across multiple continents.

Entersekt enables secure digital transactions for leading financial institutions globally. We exist to create a world where everyone can transact digitally without fear or compromise. Currently, we protect the digital transactions of over 210 million active users on our platform and hold 120 active patents that recognize innovation in digital security, payments, and user experience. Entersekt offers customers secure authentication and digital payments experiences that remove unnecessary friction. Entersekt has a diverse product portfolio and aggressive roadmap that positions the company well to sustain competitive advantage as it expands globally with emphasis on North America and European markets.

The Ideal Candidate

At Entersekt we rely on insightful data to inform our software product design. We're seeking an experienced data scientist to join our team and help us use data to drive business decisions. The ideal candidate will have experience in data science with a strong foundation in statistical analysis machine learning and data visualization. They will have natural curiosity, creative problem-solving mind and will be able to work independently and as part of a team. The ability to communicate and evangelize highly technical matters in a lucid manner to internal and external audiences including clients, prospects and analysts is an important skill for this role. Passion to solve real-world problems in the banking and financial services industry, specifically around preventing fraud and improving customer user experience will be key success factors. As part of the product team, the data scientist will work with product managers and with the CTO office to "slice and dice" data using various methods and co-create new product visions for the future.

The Role

Objectives for this role:

• Collaborate with product managers to analyze data and identify ways to improve authentication success rates.
• Use statistical analysis and machine learning techniques to detect patterns in data that can be used to improve fraud detection.
• Work with a cross-functional team to define the next generation of Entersekt's risk and fraud engine, using data science techniques to improve the accuracy and efficiency of the engine.
• Be at the forefront of championing a data-driven culture at Entersekt by communicating the value of data science to stakeholders and encouraging the use of data-driven decision-making.
• Stay up to date on the latest data science trends, technologies, and best practices, to ensure that the company is using the most effective data science techniques.
  
  

• 3 - 5+ years' experience in all aspects of the data science lifecycle from data collection to model deployment.
• Strong foundation in statistical analysis, machine learning, and data visualization.
• Bachelor's degree in computer science, computer engineering or information systems with coursework in one of the data science related disciplines.
• Hands-on experience with a variety of data science tools and techniques such as Python, R, SQL and Hadoop.
• Advanced experience in pattern recognition and predictive modeling.
• Proven ability to work effectively in a dynamic, fast-paced environment that has several product portfolios.
  
  

• Healthy self-esteem, you will be challenged by some bright minds on a regular basis.
• Excellent communication and presentation skills, you will need to translate your analysis findings to internal stakeholders.
• Deeply analytical and ability to see patterns.
• An attitude of being proud of the final deliverable and taking ownership.
• Ability to plan and keep to the deadline or raise flags early if that is at risk.