72 Data Scientist jobs in Cape Town

At Monocle, we believe work is more than a job. It is a chance to make a difference in the world of finance. An opportunity to fulfil your potential. To make friendships with ambitious, positive, likeminded people. To gain invaluable industry experience and learn critical skills that will make you a highly sought-after management consultant.

Monocle is a people-centric, independent consulting firm, specialising in banking and insurance. We understand that our greatest asset is our people and because of this, we do things a bit differently.

Monocle embraces an ongoing and active approach to amplifying the talents of our people, empowering them to unlock their full potential and feel fulfilled in their careers. Our vibrant culture thrives through our shared growth mindset, collaboration, support, and social connection, fostering a space where everyone can flourish. We are committed to continuous learning and provide ongoing technical training, industry certification support, and personal development opportunities through mentorship and executive engagement. Ultimately, we strive to create an environment that nurtures ambition, supports well-being, embraces diversity, upholds integrity, and inspires individuals to make a positive and lasting impact on the world around us.

Unlimited training and development - Investment in our peoples development is at the heart of Monocles company ethos. That is why we prioritise the upskilling of every employee.

Unparalleled growth and exposure - Monocle is uniquely positioned in the market to undertake projects across a wide spectrum of critical and exciting areas of the financial services industry. Our consultants deliver mission critical projects at the most prestigious banks and insurers in Johannesburg, Cape Town, London and Amsterdam.

Unique and vibrant company culture - At Monocle, we believe friends work better together than colleagues. We love nothing more than partaking in a wide variety of activities through our company sponsored clubs.

Ultra-competitive compensation - At Monocle, we want the best talent to join our team, so we understand that those individuals need to be recognised and rewarded for their true value.

We are seeking a highly skilled and motivated Data Scientist with a strong background in Generative AI and Machine Learning to join our team. The ideal candidate will play a critical role in developing, deploying, and scaling AI-powered applications, leveraging the latest advancements in generative AI and MLOps. This role requires proficiency in both backend and frontend development, deep understanding of vector databases, and hands-on experience with leading-edge GenAI tools and frameworks.

Design, develop, and deploy Generative AI applications using tools like Azure OpenAI Service , LangChain , and LangFuse

Build full-stack AI-powered solutions, including backend services and frontend interfaces

Work with Weaviate and other vector databases for storage and retrieval of embeddings

Implement and manage MLOps pipelines to support scalable model training and deployment

Create and optimize text and data embeddings for use in retrieval-augmented generation (RAG) and other NLP applications

Apply ML techniques to solve business problems, perform data analysis, and build predictive models

Collaborate with cross-functional teams including product, engineering, and business stakeholders to identify opportunities for AI-driven innovation

Monitor, evaluate, and continuously improve AI models and application performance

Stay up-to-date with advancements in AI/ML research and tools, especially in the GenAI space

Strong proficiency in Python programming

Demonstrated experience in building and deploying full-stack applications (both backend and frontend)

Hands-on experience with:

LangChain

LangFuse

Weaviate or similar vector databases

Solid understanding of embedding models and vector search concepts

Practical experience with MLOps tools and best practices for deploying and maintaining ML pipelines

Working knowledge of traditional machine learning algorithms and statistical modelling

Experience with cloud environments, especially Microsoft Azure

Excellent problem-solving skills and ability to work in an agile, collaborative environment

Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders

Bachelors in Mathematics, Mathematical Statistics, Computer Science, Electronic/Computer Engineering, Actuarial Science or related field.Strong preference for a post graduate qualification.

3+ years' experience in a similar role in Consulting, Banking or Financial Services.

The ideal Monocle Consultant also :

Has an enquiring mind and is eager to learn and improve their professional skillset.

Is able to work in a dynamic environment where one day never looks like another.

Is enthusiastic in their approach to their work.

Regards themselves as a high performer.

Is an excellent communicator with exceptional verbal and written communication skills.

Works well under pressure to meet client objectives.

Is sociable and enjoys interacting with others, both at work and at social events.

Works well independently and in a team.

During the interview process, you will meet with different Monocle representatives. A critical aspect of the interview process will be determining whether Monocle will be a good fit for you and your career aspirations, so please come prepared with any questions you may have.

A 45-Minute, 60-questions, online competency assessment test.

A personal meeting with People & Culture to get to know you and tell you more about Monocle.

To discuss your skills, business knowledge, experience, project fit and the role requirements.

A discussion with either our CEO, COO or CFO on various topics.

A final offer is made by the P&C team to the candidate.

*Please note that on clicking 'Apply Now' you will be redirected to our third-party career portal

Let's Write Africa's Story Together!

Old Mutual is a firm believer in the African opportunity and our diverse talent reflects this.

Job Description

Key Responsibilities

• Data Analysis & Interpretation:
  • Analyze large and complex data sets to identify trends, patterns, and insights that drive business decisions.
  • Develop and maintain dashboards, reports, and visualizations to effectively communicate findings to stakeholders.
• Predictive Modeling:
  • Design, build, and validate predictive models to support the Next Best Action engine and goal recommender.
  • Continuously refine models based on feedback and new data to ensure accuracy and relevance.
• Collaboration:
  • Work closely with cross-functional teams, including product owners, data engineers, and business stakeholders, to understand data needs and deliver actionable insights.
  • Provide mentorship and guidance to junior analysts within the team.
• Innovation & Improvement:
  • Stay up-to-date with the latest trends and technologies in data analytics and financial services.
  • Identify opportunities for process improvements and automation within the analytics workflow.
• Customer-Centric Approach:
  • Leverage data to enhance customer experiences and engagement through personalized recommendations and insights.
  • Contribute to the development of our chatbot to ensure it provides valuable, data-driven financial advice to customers.

Minimum Requirements

• Education:
  • Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
• Experience:
  • 5+ years of experience in data analysis, preferably within the financial services industry.
  • Proven experience in building and deploying predictive models.
  • Strong knowledge of data analytics tools and programming languages such as SQL, Python, R, and relevant data visualization tools (e.g., Tableau, Power BI).
• Skills:
  • Excellent analytical and problem-solving skills with a keen eye for detail.
  • Strong communication skills, with the ability to present complex data insights to non-technical stakeholders.
  • Ability to work collaboratively in a fast-paced, dynamic environment.
  • Experience with big data technologies (e.g., Hadoop, Spark) is a plus.
• Personal Attributes:
  • Self-motivated, proactive, and eager to learn and grow.
  • Customer-focused with a passion for improving financial wellness through data-driven insights.
  • Strong organizational skills and the ability to manage multiple projects simultaneously.

Skills

Competencies

Education

Closing Date

The appointment will be made from the designated group in line with the Employment Equity Plan of Old Mutual South Africa and the specific business unit in question.

The Old Mutual Story!

We are looking for a curious, dependable, and impact-driven Intermediate Data Scientist to step confidently into a role that blends advanced analytics, stakeholder communication, and team contribution. This is an exciting opportunity to play a leading role in shaping our data science environment while delivering high-impact models and insights that inform real business decisions. You’ll work at the intersection of data and strategy—helping to define how data science is applied across the organization.

In this role, you’ll collaborate with Software Engineers, Data Engineers, Data Analysts, Product Owners and decision-makers to scope, build, and deliver solutions using advanced statistical and machine learning models. You’ll be responsible for turning complex data into actionable recommendations and contributing to the design and implementation of data science frameworks using cutting-edge technologies. With a strong passion for modeling and experimentation, you’ll bring a scientific approach to solving business problems in a fast-paced FinTech environment.

Beyond technical delivery, this role is about how you show up in the team – sharing knowledge, offering mentorship, fostering collaboration, and bringing energy and positivity to our day-to-day culture. As a trusted advisor and a core member of the Data & Analytics team, you’ll play a key part in building not just data solutions, but a data-driven, collaborative, and innovative way of working.

Duties and Responsibilities:

• Problem Framing & Business Understanding
  • Collaborate with stakeholders to understand business problems and translate them into data science opportunities.
  • Define success criteria and hypotheses for modeling efforts.
  • Proactively recommend data science applications that add business value.
• Model Development & Analysis
  • Build, test, and deploy models for prediction, classification, clustering, or segmentation.
  • Use appropriate techniques (e.g., regression, decision trees, time series, NLP, or unsupervised learning) with an understanding of trade-offs.
  • Apply rigorous validation and performance testing to ensure robustness.
  • Design and implement experiments and conduct A/B testing to evaluate hypotheses.
• Insight Generation & Communication
  • Develop statistical models and algorithms to extract insights from complex datasets.
  • Interpret model outputs in the context of the business and communicate results to non-technical audiences.
  • Create clear, actionable summaries and data stories that drive decisions.
  • Highlight not just results, but implications and recommended next steps.
• Collaboration & Culture Building
  • Collaborate with cross-functional teams to identify and analyze business problems.
  • Contribute positively to team culture through collaboration, energy, and willingness to help others.
  • Actively participate in team ceremonies and learning opportunities.
  • Support junior team members through code reviews, brainstorming, or informal mentoring.
  • Model accountability, open communication, and psychological safety.
• Technical Development & Governance
  • Follow reproducible workflows (e.g., version control, environment tracking, documentation).
  • Ensure models and codebases are clean, well-documented, and scalable.
  • Stay up to date with new techniques and apply relevant advances to your work.

Minimum Requirements:

In order to be considered for this position, the following requirements must be met:

• Bachelor’s degree in Computer Science, Statistics, or a related field.
• 2-3 years’ experience working as a Data Scientist in the FinTech industry.
• Proficient in Python, with strong knowledge of key libraries
• Skilled in SQL and experience working with structured data in cloud-based environments (BigQuery exposure is advantageous).
• In-depth knowledge of statistical modelling, machine learning, and data mining techniques.
• Excellent problem-solving skills and the ability to work in a fast-paced environment.
• Ability to independently manage the lifecycle of a data science project from scoping to delivery.

Technical Skills:

• Familiarity with data visualization tools such as Power BI.
• Strong programming skills in Python.
• Experience with cloud data tools (BigQuery and AWS).
• Experience with big data technologies such as Spark is a plus.
• Exposure to MLOps principles (e.g., model tracking, pipelines, CI/CD).
• Experience collaborating with BI teams and integrating data science into dashboards.
• Familiarity with Git, Jira, and Confluence.
• Understanding of experimentation and A/B testing design.

Behavioural Competencies:

• Strong communicator who can simplify complex concepts for business audiences.
• Naturally collaborative, with a desire to support others and share knowledge.
• Detail-oriented but able to keep the bigger picture in mind.
• Brings a positive presence to the team—encouraging, empathetic, and respectful.
• Proactive and curious; always looking for ways to add value.

Performance Expectations:

• Deliver models and insights that directly influence business outcomes.
• Communicate findings in a clear, structured, and compelling way.
• Take ownership of delivery timelines and project accountability.
• Contribute to a supportive, high-performing team environment.
• Share knowledge, support peers, and model a growth-oriented mindset.
• Be recognized by both the team and stakeholders as a reliable, collaborative, and positive contributor.

• 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.

• Develop and implement machine learning models to support product development and business decision-making.
• Analyse large and complex datasets to identify patterns, trends, and actionable insights.
• Collaborate with Software Developers, Product Managers, and Data Engineers to design data-driven solutions.
• Evaluate and improve model performance through rigorous testing and optimization.
• Communicate findings and recommendations to both technical and non-technical stakeholders.

• Proven experience as a Data Scientist with exposure to real-world data science projects.
• Solid understanding of machine learning techniques and statistical modelling.
• Proficiency in Python and relevant libraries such as scikit-learn, TensorFlow, or PyTorch.
• Strong SQL skills and familiarity with data wrangling, feature engineering, and model deployment.
• Experience working with cloud platforms, preferably Microsoft Azure.
• Excellent problem-solving skills with the ability to translate complex data into clear insights.

• • Data Scientist

    Turn sports data into winning strategies with advanced algorithms and machine learning
    Cape Town | R1 200 000 - R1 300 000 per annum | 08:00am 17:00pm

    About Our Client
    Our client is an innovative sports technology company pushing the boundaries of performance analytics. By combining cutting-edge data science with elite-level sports expertise, they provide actionable insights that empower coaches, players, and broadcasters. The team is driven by a passion for precision, innovation, and unlocking new competitive advantages through data.

    The Role: Data Scientist
    As a Data Scientist, you will be responsible for designing, developing, and evaluating advanced algorithms and models that transform raw sensor data into meaningful insights. This role involves close collaboration with engineers and sports scientists to support predictive analytics that inform strategies in elite sports.

    Key Responsibilities

    • Design, develop, and evaluate signal processing algorithms to deliver insights for players, coaches, and broadcasters

    • Build and refine algorithms under the guidance of senior team members

    • Develop and maintain documentation of the data science architecture and algorithms

    • Partner with sports scientists to collect and validate sensor data

    • Develop and train machine learning models to provide predictive insights into team strategies

    About You

    • BEng/BSc or higher in Electronic Engineering, Mathematics, or Computer Science

    • Strong knowledge of signal processing concepts (filtering, Nyquist frequencies, time-frequency transformations)

    • Understanding of algorithm performance evaluation techniques (e.g., receiver-operating-curves)

    • Experience with machine learning algorithms (regression, decision trees, SVMs, neural networks)

    • Proficiency in Python, MATLAB, Octave, or R for data analysis and simulations

    • Excellent time management and attention to detail

    • Hands-on, technically curious, and an effective communicator

    • Strong interest in sports trends and analytics

At Monocle, we believe work is more than a job. It is a chance to make a difference in the world of finance. An opportunity to fulfil your potential. To make friendships with ambitious, positive, likeminded people. To gain invaluable industry experience and learn critical skills that will make you a highly sought-after management consultant.

Monocle is a people-centric, independent consulting firm, specialising in banking and insurance. We understand that our greatest asset is our people and because of this, we do things a bit differently.

Monocle embraces an ongoing and active approach to amplifying the talents of our people, empowering them to unlock their full potential and feel fulfilled in their careers. Our vibrant culture thrives through our shared growth mindset, collaboration, support, and social connection, fostering a space where everyone can flourish. We are committed to continuous learning and provide ongoing technical training, industry certification support, and personal development opportunities through mentorship and executive engagement. Ultimately, we strive to create an environment that nurtures ambition, supports well-being, embraces diversity, upholds integrity, and inspires individuals to make a positive and lasting impact on the world around us.

Unlimitedtraininganddevelopment - Investment in our peoples development is at the heart of Monocles company ethos. That is why we prioritise the upskilling of every employee.

Unparalleledgrowthandexposure- Monocle is uniquely positioned in the market to undertake projects across a wide spectrum of critical and exciting areas of the financial services industry. Our consultants deliver mission critical projects at the most prestigious banks and insurers in Johannesburg, Cape Town, London and Amsterdam.

Uniqueandvibrantcompanyculture - At Monocle, we believe friends work better together than colleagues. We love nothing more than partaking in a wide variety of activities through our company sponsored clubs.

Ultra-competitive compensation - At Monocle, we want the best talent to join our team, so we understand that those individuals need to be recognised and rewarded for their true value.

We are seeking a highly skilled and motivated Data Scientist with a strong background in Generative AI and Machine Learning to join our team. The ideal candidate will play a critical role in developing, deploying, and scaling AI-powered applications, leveraging the latest advancements in generative AI and MLOps. This role requires proficiency in both backend and frontend development, deep understanding of vector databases, and hands-on experience with leading-edge GenAI tools and frameworks.

Design, develop, and deploy Generative AI applications using tools like Azure OpenAI Service , LangChain , and LangFuse

Build full-stack AI-powered solutions, including backend services and frontend interfaces

Work with Weaviate and other vector databases for storage and retrieval of embeddings

Implement and manage MLOps pipelines to support scalable model training and deployment

Create and optimize text and data embeddings for use in retrieval-augmented generation (RAG) and other NLP applications

Apply ML techniques to solve business problems, perform data analysis, and build predictive models

Collaborate with cross-functional teams including product, engineering, and business stakeholders to identify opportunities for AI-driven innovation

Monitor, evaluate, and continuously improve AI models and application performance

Stay up-to-date with advancements in AI/ML research and tools, especially in the GenAI space

Strong proficiency in Python programming

Demonstrated experience in building and deploying full-stack applications (both backend and frontend)

Hands-on experience with:

LangChain

LangFuse

Weaviate or similar vector databases

Solid understanding of embedding models and vector search concepts

Practical experience with MLOps tools and best practices for deploying and maintaining ML pipelines

Working knowledge of traditional machine learning algorithms and statistical modelling

Experience with cloud environments, especially Microsoft Azure

Excellent problem-solving skills and ability to work in an agile, collaborative environment

Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders

Bachelors in Mathematics, Mathematical Statistics, Computer Science, Electronic/Computer Engineering, Actuarial Science or related field.Strong preference for a post graduate qualification.

3+ years' experience in a similar role in Consulting, Banking or Financial Services.

The ideal Monocle Consultant also :

Has an enquiring mind and is eager to learn and improve their professional skillset.

Is able to work in a dynamic environment where one day never looks like another.

Is enthusiastic in their approach to their work.

Regards themselves as a high performer.

Is an excellent communicator with exceptional verbal and written communication skills.

Works well under pressure to meet client objectives.

Is sociable and enjoys interacting with others, both at work and at social events.

Works well independently and in a team.

During the interview process, you will meet with different Monocle representatives. A critical aspect of the interview process will be determining whether Monocle will be a good fit for you and your career aspirations, so please come prepared with any questions you may have.

A 45-Minute, 60-questions, online competency assessment test.

A personal meeting with People & Culture to get to know you and tell you more about Monocle.

To discuss your skills, business knowledge, experience, project fit and the role requirements.

A discussion with either our CEO, COO or CFO on various topics.

A final offer is made by the P&C team to the candidate.

*Please note that on clicking 'Apply Now' you will be redirected to our third-party career portal