1,437 Senior Data Scientist jobs in South Africa

Overview

Unifi is redefining credit in Africa with simple, fast personal loans delivered through online, mobile and branch channels. We make life easy for thousands of clients across Zambia, Kenya, Uganda and South Africa. Unifi combines exceptional client service with the very best tech and data analytics.

Unifi is looking for a Data Scientist with expertise in Python, Google Looker, and BigQuery to help turn complex data into insights that drive smarter decisions. In this role, you’ll collect, analyze, and interpret data, uncovering trends and delivering insights that shape business strategy. You’ll work closely with stakeholders to design impactful solutions, optimize processes, and improve overall performance.

At Unifi, we value curiosity, simplicity, and bold ideas. If you’re self-driven, adventurous, and passionate about African business, this is your opportunity to make a real impact.

• Data Collection & Preparation: Collect, extract, and compile data from multiple sources, ensuring accuracy and completeness. Clean and transform raw data into structured datasets for analysis. Identify and resolve data quality issues, inconsistencies, and anomalies. Work with SQL, Python, and BigQuery, while staying up to date with new trends and tools in data analytics.
• Data Analysis & Insights: Perform exploratory and statistical analysis to identify patterns, trends, and relationships. Use data visualization techniques to interpret and present findings clearly. Analyse large datasets to deliver actionable insights and recommendations. Support scorecard development, maintenance, testing, and reporting. Provide input into credit policy proposals and client limit management through data-driven analysis.
• Business Decision Support: Collaborate with stakeholders to understand business requirements and translate them into analytical solutions. Provide analytical support for initiatives such as market analysis, customer segmentation, and performance tracking. Identify opportunities to improve processes, drive efficiencies, and optimize revenue.
• Continuous Learning & Development: Keep up with best practices, emerging technologies, and industry trends in data science and analytics. Expand expertise in statistical analysis, data modeling, and visualization tools. Actively participate in professional development through training, workshops, and knowledge sharing.

• Bachelor’s or Master’s degree in Mathematics, Statistics, Computer Science, Data Analytics/Science, or a related field.
• 3+ years’ proven experience as a Data Scientist or in a similar role, ideally within credit or financial services.
• Proficiency in GCP (Google Cloud Platform), BigQuery, SQL, Python, R, and data visualization tools such as Google Looker.
• Strong analytical and problem-solving skills, with the ability to work with large datasets.
• Experience in statistical analysis and data modeling.
• Excellent communication and presentation skills.
• Solid working knowledge of Microsoft Excel and other data manipulation tools.
• Familiarity with data governance and awareness of data privacy regulations is advantageous.

Overview

Data Scientist – Badger Holdings

George, Western Cape (On-site | Office-based)

At Badger Holdings, we don’t just crunch numbers, we use data to reshape insurance and solve real-world problems. We’re looking for a Data Scientist who’s ready to take ownership of the full machine learning lifecycle: from raw data, to insights, to deployed models that actually move the needle.

You’ll be responsible for the development and deployment of machine learning solutions that tackle real business challenges. This means data preparation, exploratory data analysis, feature engineering, model development, deployment, monitoring — and doing it all without needing your hand held.

• Prep, clean, transform and engineer features from raw data
• Run exploratory data analysis to uncover insights & shape models
• Build, validate and deploy machine learning models
• Monitor and retrain models to stay ahead of drift
• Troubleshoot and maintain deployed solutions
• Document pipelines, models and processes clearly
• Create dashboards & reporting tools for business teams

Location: North West

Industry: IT

Salary: £55,000 - £62,000 per annum + Bonus + Benefits

Posted: 27/08/2024

We are seeking a Data Scientist to join our team in Manchester. This role offers a hybrid working model with 1 day a week in the office.

Responsibilities include:

• Understanding operational problems, gathering business requirements, and designing data-driven solutions.
• Working on initiatives like Personalised Credit Matching using machine learning models to enhance customer experience.
• Collaborating with stakeholders to translate business needs into effective data science projects.
• Building strong relationships with business areas to leverage data for performance improvements.
• Producing insights to optimize channels, evaluate opportunities, and understand customer value.
• Presenting findings to both technical and non-technical audiences.
• Staying updated with industry trends and visualization technologies.

Ideal candidates will have experience in converting business requirements into impactful data science solutions, working in fast-paced environments, and possessing strong technical skills.

Technical skills required:

• Proficiency in Python and/or R
• Understanding of analytical techniques and their applications
• Good knowledge of SQL and relational databases
• Data modeling and visualization expertise
• Experience working with large, complex datasets

This is a fantastic opportunity for passionate Data Scientists to grow within a forward-thinking organization that offers state-of-the-art technologies and a competitive benefits package, including an annual bonus.

Please submit your CV today for immediate consideration.

At Ascent People, we are committed to equality and diversity. We ensure job criteria are relevant and do not discriminate based on gender, age, disability, race, ethnicity, religion, sexual orientation, or social status.

Recruiter: Nadine Bramley

Phone:

Email:

1. Data Analysis and Modeling:
   Develop and deploy machine learning, AI, and algorithms to extract insights, predict outcomes, and optimize processes.
   Data analysis, data exploration, and data preprocessing to extract valuable information from large datasets.
   Apply statistical techniques and hypothesis testing to validate findings.
2. Data Strategy and Planning:
   Define data-driven objectives and formulate data strategies aligned with business goals.
   Identify KPIs and establish data collection and measurement protocols.
   Engineer features and create data pipelines to prepare and clean data for modeling.
   Ensure data availability and quality.
3. Model Evaluation and Deployment:
   Evaluate model performance and fine-tune models for improved accuracy.
   Deploy models and monitor their ongoing performance.
   Implement best practices for model version control and management.
   Integrate proven models into business processes and software products.
   Remove the requirement for human intervention to implement the model.
4. Cross-Functional Collaboration:
   Collaborate with Business Analysts, Data Engineers, and Domain Experts to understand and address specific business problems.
   Communicate findings and insights in a clear and actionable manner.
5. Leadership and Mentorship:
   Lead and mentor Junior Data Scientists.
   Participate in knowledge-sharing and training programs that enhance the data science capabilities of the team.
   Foster a collaborative and innovative work environment.
6. Data Privacy and Compliance:
   Ensure data privacy and compliance with relevant regulations and best practices.
   Develop and enforce data security protocols.

1. Computer Science / Data Science / related Degree or master’s qualification.
2. Certified Data Scientist / other certification (advantageous).
3. Hands-on machine learning and statistical analysis experience.
4. Proficient in data analysis, modeling tools and libraries e.g., Python, R.
5. Knowledge of data manipulation and visualization.
6. Data preprocessing, feature engineering, and model evaluation expertise.
7. Excellent problem-solving skills.
8. Critical-thinking skills.
9. Strong communication and interpersonal skills.

By applying for this position, you consent in terms of the Protection of Personal Information Act (POPI Act) to your personal information being obtained, utilized, and stored by the Company through inter alia, reference checks, credit checks, and trace reports.
Should you not hear from us within 7 days, please consider your application unsuccessful.

Reference: DUR -MN-1

Our client is seeking a Data Scientist with a strong background in machine learning. The ideal candidate must be willing to travel to the office daily.

Responsibilities:

Data Analysis and Modelling:

• Develop and deploy machine learning and artificial intelligence models and algorithms to extract insights, predict outcomes, and optimize processes.
• Conduct in-depth data analysis, data exploration, and data preprocessing to extract valuable information from large datasets.
• Apply statistical techniques and hypothesis testing to validate findings.

• Collaborate with stakeholders to define data-driven objectives and formulate data strategies aligned with business goals.
• Identify key performance indicators (KPIs) and establish data collection and measurement protocols.

• Engineer features and create data pipelines to prepare and clean data for modelling.
• Work with data engineering teams to ensure data availability and quality.

• Evaluate model performance and fine-tune models for improved accuracy.
• Deploy models in production environments and monitor their ongoing performance.
• Implement best practices for model version control and management.
• Ensure proven models are integrated into business processes and software products.

• Collaborate with business analysts, data engineers, and domain experts to understand and address specific business problems.
• Communicate findings and insights to non-technical stakeholders in a clear and actionable manner.

• Provide leadership and mentorship to junior data scientists.
• Participate in knowledge-sharing and training programs to enhance the data science capabilities of the team.
• Foster a collaborative and innovative work environment.

• Ensure data privacy and compliance with relevant regulations and best practices.
• Develop and enforce data security protocols.

• Degree in Computer Science, Data Science, or a related field.
• Proven experience in data science roles, including hands-on experience with machine learning, deep learning, and statistical analysis.
• Proficiency in data analysis and machine learning tools and libraries e.g. Python, R.
• Strong programming skills and knowledge of data manipulation and visualization.
• Expertise in data preprocessing, feature engineering, and model evaluation.
• Excellent problem-solving and critical-thinking skills.
• Strong communication and interpersonal skills to effectively collaborate with various stakeholders.
• Relevant certifications e.g. Certified Data Scientist etc. are a plus.

R 5000 - R 55000 - Monthly

• We offer both remote and hybrid work opportunities
• Intellinexus is an SME, therefore you get a lot of exposure to different technologies, solutions and techniques during projects.
• Intellinexus supports career development and growth of its employees, therefore time and money is invested to grow their consultants in their careers.

This is a data science role focusing on acquiring as many quality clients as possible through performance and brand marketing, in the most cost-efficient way possible.

• We have all the data we need to understand, measure and influence client acquisition: Work across the end-to-end client acquisition journey, from off platform to product conversion, to ensure data is created and consumed in a way that enables you to bring them together to fuel your insights and modelling. Ensure data quality and interoperability is owned at source by working with engineers, architects, and marketers across the ecosystem. Success will be measured by the completeness and quality of data, facilitating a comprehensive view of the client acquisition journey.
• We can reliably and predictably attract the targeted segments of the market onto our platform: Collaborate with campaign managers to iterate on marketing campaigns, refine our segments and establish the most cost-effective way to bring prospective clients to our website to evaluate our products. Produce insights, run experiments, and develop predictive models to optimise channel specific campaign performance and cross channel spend. E.g. What budget and channel allocations do we need to hit our client acquisition and cost of acquisition targets for segment X next quarter? Success will be measured in the number of quality clients acquired through each campaign and efficiency of the spend on it (e.g. client LTV / CAC, campaign ROI).
• Prospective clients have all the relevant information and advice they need to understand their needs and build confidence in our products: Work closely with UX designers and user researchers to create the best landing and evaluation journey experience for prospective clients, optimising content and journey’s that are best suited for each segment. Involve user researchers to uncover the why behind the what. E.g. Which web pages contribute most to an acquisition? Do people prefer handholding through our Call Centre Agents or directing their own journey through long form web pages? Success will be measured by conversion of on-platform prospects who enter the qualification funnel and through qualitative surveys about their confidence and experience.
• Once a client decides, the rest of the product onboarding process is so transparent and frictionless, there’s almost no drop off: Work with product houses to identify points in the product application and onboarding journey that cause drop off. Work with user researchers to optimise for maintaining transparency and confidence, while addressing any accessibility needs. E.g. Which parts of the onboarding process require the longest time, how can data and ML be used to reduce or even eliminate it? Success will be measured in completion times and rates in this final step of the process.
• As a team, we always know how well we’re performing and (roughly) why: Create datasets, metric frameworks and visualisations that together provide information-rich stories about our activities and their performance. These stories should cover everything from the digital marketing channels and partners we’re using, to the format and nature of the content (e.g. video vs image, animal photos vs people photos). Leverage computer vision and/or NLP as a service to enrich your data to support this content rich analysis. Success will be measured in the depth of understanding, and minutes it takes, for the team to learn about their key metrics and drivers.

• Data Scientists are the people who bring practices from empirical science to life to drive the iterative product development lifecycle. They embed within teams they support, achieving a marriage of minds with their stakeholders and an integration of objectives and workflows. They work across the team with UX researchers, feature engineers, domain experts and business, product, and marketing managers, to create data about user behaviours, discover unmet needs, set metrics that measure performance and design & execute experiments to generate learnings and evidence their success (or lack thereof).
• This is a role where mastery in data wrangling, metric setting, experimentation, machine learning and data storytelling are combined to enable product teams to become learning machines. This requires a thoughtful application of craft across the entire data journey, from data creation to changing our campaigns. Whether it’s creating data or generating learnings, training ML models, setting metrics, or collaborating on the roadmap, data scientists are critical partners to the team they embed in!

• Driving data creation: Establish the first principles and facilitate discussions about how to create data about relevant user behaviours and measure success. Design event log schemas and test their implementation.
• Wrangling data autonomously: Wrangle data into the ideal format for the necessary tool (e.g. Python, Tableau, PowerBI), no how raw and unstructured it and what lake/Lakehouse it’s stored in.
• Setting team metrics: Define holistic measurement frameworks that enable the team to explore their performance holistically and work with the team to identify and track the metrics that measure success.
• Producing insights: Identify loosely defined commercial problems and produce meaningful insights that guide iterations of the teams products and go-to-market campaigns.
• Developing ML models: Structure commercial problems into prediction problems by clarifying both what is being predicted and how that enables us to change our products or campaigns to obtain a better result. Develop and implement ML models for the highest priority prediction problems, ensuring outstanding model and product performance.
• Carrying out controlled experiments: Establish the learning goals of their team, crafting hypothesis statements and learning roadmap wherever needed. Design, execute and draw correct conclusions from experiments by confirming integrity of experiment, avoiding common pitfalls, and executing frequentist or Bayesian A/B analysis.
• Segmenting the client base: Using rule and unsupervised learning-based approaches to segment the client base so we can develop a deeper understanding of customers and build better products for them.
• Creating impactful visualisations: Produce data and interactive visualisations that enable the whole team to address their recurring reporting and insight needs, without your direct support.
• Partnering for impact: Partner with stakeholders to make sure they gain the confidence they need to drive changes in the product roadmap or ask for further insight.
• Evolving the learning mindset of the team: Create a culture of insights and learning, where everyone obsesses about their success metrics and are constantly testing and learning to better their performance.

Our aim is to help you build a successful career with us

We’re all about building strong, lasting relationships with our employees. We know that you have hopes for your future – your career, your personal development, and for achieving great things. We pride ourselves in helping our employees to realize their worth. Through Intellinexus and its clients, we provide many opportunities for growth and development.

We are looking for a talented Data Scientist to join our team, responsible for analyzing and interpreting complex data to inform business decisions and drive growth. The successful candidate will have a strong background in data analysis, machine learning, and statistics, with a proven track record of delivering high-quality insights and recommendations. The Data Scientist will work closely with cross-functional teams, including product, engineering, and business development, to identify opportunities for data-driven innovation and develop strategic plans to execute on these opportunities.

• Analyze and interpret complex data to inform business decisions and drive growth
• Develop and maintain large-scale data systems, including data warehouses, data lakes, and data pipelines
• Collaborate with engineers to develop and implement data-driven products and solutions
• Work with product managers to develop product roadmaps and prioritize features and requirements
• Develop and maintain relationships with key stakeholders, including business leaders, product managers, and engineering teams
• Communicate complex data insights and recommendations to non-technical stakeholders, including business leaders and product managers
• Stay up-to-date with the latest advancements in data science, machine learning, and AI, applying this knowledge to drive innovation and improvement in data-driven products and solutions
• Develop and maintain predictive models and algorithms to drive business growth and innovation

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or related field
• 3+ years of experience in data science, machine learning, or statistics, with a focus on data analysis and interpretation
• Strong background in data analysis, machine learning, and statistics, with expertise in areas such as predictive modeling, data visualization, and data mining
• Experience with data science frameworks and tools, such as Python, R, or SQL
• Strong programming skills in languages such as Python, R, or Java
• Experience with cloud-based technologies, such as AWS or Google Cloud
• Strong understanding of software engineering principles, including design patterns, testing, and version control
• Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams

Technical Skills:

• Machine learning: supervised, unsupervised, and reinforcement learning
• Cloud-based technologies: AWS, Google Cloud, Azure, etc.

Full time

Johannesburg

This is a remote position.

Ringier Data Technology Department is looking for a Data Scientist to join our team.

Our team leverages the latest models to predict financial figures or the best price for an advertisement, create user-facing chatbots and much more applications. We’re also working with cutting-edge technologies, like LLMs, trying to create applications that will drastically increase the visibility of Ringier’s brands.

• You work with various datasets from different Ringier companies in different business divisions across publishing and marketplaces and in different regions across continents.
• You choose, improve, and apply various methods from statistics, machine, and deep learning technologies in order to solve business problems.
• You model the data of our users, their interests and online behaviour as well as the data of the different Ringier’s business units in order to serve the business demands, and enable the future business models.
• You work closely with cross-functional teams to develop prototypes and products for cross-portfolio use cases.
• You communicate and visualise the value of data by describing the findings or the way how techniques work to both technical and non-technical audiences.
• You keep closely following research and engineering developments mostly in the NLP field, like HuggingFace, LLMs roll in the relevant technologies and methodologies to keep our modern technology landscape up to date.

• You have a degree (MS, Ph.D.) in computer science, statistics, mathematics or a comparable degree program or equivalent work experience.
• You have a strong record in applying Machine Learning to real-world datasets in a productive environment and are familiar with the main ML frameworks (TensorFlow, Torch, XGBoost, LightGBM, …) and have strong experience in Python.
• You have worked with LLMs and frameworks like Langchain. You know the best practices and keep following the field so that you use the latest ones.
• You have deep knowledge of the latest advances in the NLP domain.
• Experience with Palantir Foundry is a plus.
• Experience in software development and confidence in developing the full ML model lifecycle from research to production ensuring aspects such as reproducibility and scalability (git, dvc, Docker, Amazon Web Services) is a plus.
• You have full professional proficiency in English.
• You’re a team player and at the same time can be independent and take responsibility for your tasks. Structured way of working and creativity complete your profile.

• We are fully remote! Work from anywhere in the world within a 3 hour SAST time zone.
• We have co-working spaces in Cape Town, Mauritius, Kenya & Nigeria.
• A cutting-edge development stack is waiting for your code contribution.
• You will be working with over 80+ highly skilled technical minds (and expanding).
• Backing of the international media powerhouse Ringier AG, which allows us to access world class development resources, shared knowledge and a wealth of international business insights.
• Our teams work with a wide range of tech stacks.
• We are committed to the future growth prospects of our employees by allowing autonomy, flexibility and an opportunity to master your respective skill.

Executive

Full-time

Information Technology

IT Services and IT Consulting

This is a remote position.

Ringier Data Technology Department is looking for a Data Scientist to join our team.

Our team leverages the latest models to predict financial figures or the best price for an advertisement, create user-facing chatbots and much more applications. We’re also working with cutting-edge technologies, like LLMs, trying to create applications that will drastically increase the visibility of Ringier’s brands.

• You work with various datasets from different Ringier companies in different business divisions across publishing and marketplaces and in different regions across continents.
• You choose, improve, and apply various methods from statistics, machine, and deep learning technologies in order to solve business problems.
• You model the data of our users, their interests and online behaviour as well as the data of the different Ringier’s business units in order to serve the business demands, and enable the future business models.
• You work closely with cross-functional teams to develop prototypes and products for cross-portfolio use cases.
• You communicate and visualise the value of data by describing the findings or the way how techniques work to both technical and non-technical audiences.
• You keep closely following research and engineering developments mostly in the NLP field, like HuggingFace, LLMs roll in the relevant technologies and methodologies to keep our modern technology landscape up to date.

• You have a degree (MS, Ph.D.) in computer science, statistics, mathematics or a comparable degree program or equivalent work experience.
• You have a strong record in applying Machine Learning to real-world datasets in a productive environment and are familiar with the main ML frameworks (TensorFlow, Torch, XGBoost, LightGBM, …) and have strong experience in Python.
• You have worked with LLMs and frameworks like Langchain. You know the best practices and keep following the field so that you use the latest ones.
• You have deep knowledge of the latest advances in the NLP domain.
• Experience with Palantir Foundry is a plus.
• Experience in software development and confidence in developing the full ML model lifecycle from research to production ensuring aspects such as reproducibility and scalability (git, dvc, Docker, Amazon Web Services) is a plus.
• You have full professional proficiency in English.
• You’re a team player and at the same time can be independent and take responsibility for your tasks. Structured way of working and creativity complete your profile.

• We are fully remote! Work from anywhere in the world within a 3 hour SAST time zone.
• We have co-working spaces in Cape Town, Mauritius, Kenya & Nigeria.
• A cutting-edge development stack is waiting for your code contribution.
• You will be working with over 80+ highly skilled technical minds (and expanding).
• Backing of the international media powerhouse Ringier AG, which allows us to access world class development resources, shared knowledge and a wealth of international business insights.
• Our teams work with a wide range of tech stacks.
• We are committed to the future growth prospects of our employees by allowing autonomy, flexibility and an opportunity to master your respective skill.

Executive

Full-time

Information Technology

IT Services and IT Consulting