Senior Data Scientist

Zensar Technologies; Johannesburg; Hybrid; ZAR 900,000 - 1,700,000; Full time

Job summary

Zensar Technologies is seeking a Senior Data Scientist in Johannesburg to design, develop, and optimise machine learning, AI, and decisioning solutions that strengthen risk management and drive commercial performance.

You will collaborate across PPB and Digital channels, using Databricks, MLflow, and Generative AI to deliver production-ready models and reusable features that scale across enterprise domains.

Qualifications

• Proven record of delivering end-to-end data science projects from ideation to production.
• Strong background in predictive and prescriptive analytics and decisioning.
• Experience with Databricks platform including notebooks and workflows.

Responsibilities

• Identify high-impact analytical opportunities with cross-functional teams.
• Develop, train, and optimise ML models using Databricks and MLflow.

Skills

Advanced Python

SQL

Databricks

MLflow

Generative AI

Feature Engineering

Stakeholder Engagement

Data storytelling

Education

Master's degree in Data Science or Analytics

Tools

Databricks

Delta Tables

Databricks Workflows

Enterprise Feature Store

Job description

Drive Intelligent Decisions. Deliver Measurable Impact.

• Location: JHB
• Workplace Type: 3 days in office per week

Are you passionate about turning data into actionable business outcomes? Do you enjoy solving complex customer, risk, and operational challenges using advanced analytics, machine learning, and AI?

We're looking for an exceptional Senior Data Scientist to join our growing Analytics and AI team. In this role, you will design, develop, and optimise machine learning, AI, and decisioning solutions that improve customer experiences, strengthen risk management, and drive commercial performance across Personal & Private Banking (PPB) and Digital channels.

This is an exciting opportunity to work with cutting-edge technologies including Databricks, MLflow, Feature Engineering, Generative AI, Large Language Models (LLMs), and Decision Science, while partnering with business leaders to solve high-value problems at scale.

Why Join Us?

• Work on strategic AI and machine learning initiatives with real business impact.
• Shape customer engagement, acquisition, retention, and cross-sell strategies through advanced analytics.
• Build reusable enterprise assets that power decision-making across the organisation.
• Leverage modern platforms including Databricks, MLflow, Delta Tables, and Enterprise Feature Stores.
• Collaborate with business, digital, product, risk, and engineering teams.
• Influence the future of AI, Machine Learning, and Decision Science within a data-driven organisation.
• Mentor and develop the next generation of Data Scientists.

What You'll Do

As a Senior Data Scientist, you'll be responsible for identifying opportunities, developing advanced analytical solutions, and delivering measurable business value through data science and AI.

Key Responsibilities

• Partner with PPB, Digital, Product, and Risk teams to identify and prioritise high-impact analytical opportunities.
• Design, develop, train, and optimise machine learning models using Databricks, MLflow, and distributed computing environments.
• Develop customer propensity, next-best-action, next-best-product, customer value, retention, and engagement models.
• Build risk, collections, fraud, and operational models that improve decision quality and business performance.
• Develop and maintain reusable feature pipelines using Databricks Feature Engineering and Delta Tables.
• Create, govern, and optimise reusable enterprise features within the Databricks Enterprise Feature Store.
• Establish feature definitions, lineage, quality controls, monitoring standards, and governance frameworks across business domains.
• Apply advanced feature engineering, feature selection, and feature importance techniques to maximise model accuracy and reuse.
• Develop optimisation and decisioning models that support customer engagement, product recommendations, and operational decision strategies.
• Conduct exploratory data analysis, statistical analysis, hypothesis testing, and model validation using Databricks notebooks and workflows.
• Perform model tuning, calibration, challenger model development, and performance benchmarking.
• Monitor model performance, stability, drift, and business impact, recommending enhancements where required.
• Develop Generative AI solutions across use cases such as customer support, document intelligence, and knowledge assistants.
• Partner closely with Machine Learning Engineers to productionise models, features, and analytical assets.
• Produce model documentation, validation reports, and governance artefacts aligned to model risk management standards.
• Mentor junior Data Scientists and contribute to modelling standards, reusable frameworks, and analytical best practices.

What Success Looks Like

Production-ready machine learning models supporting PPB and Digital business use cases

Enterprise feature libraries and reusable business features in the Databricks Feature Store

Customer decisioning models driving acquisition, retention, engagement, and cross-sell outcomes

Risk, fraud, collections, and operational models improving decision quality and business performance

Analytical insights and recommendations that influence strategic business decisions

Well-governed model documentation, validation artefacts, and monitoring frameworks

Measurable business value through deployed AI and Machine Learning solutions

Skills & Experience Required

Data Science & Machine Learning

• Machine Learning model development and optimisation
• Predictive and Prescriptive Analytics
• Experimentation and Model Validation
• Decision Science and Optimisation
• Customer Analytics and Decisioning

Databricks Expertise

• Databricks Notebooks
• Databricks Workflows
• MLflow

Programming & Data Management

• Advanced Python
• SQL
• Customer, behavioural, transactional, and digital datasets

AI & Emerging Technologies

• Generative AI
• Prompt Engineering
• Applied AI Use Cases

Business & Consulting Skills

• Data storytelling and visualisation
• Problem-solving and business consulting
• Communication and influence

What We're Looking For

We're seeking a data science professional who combines deep technical expertise with strong commercial acumen and stakeholder engagement skills.

You’ll stand out if you have:

• Proven experience developing machine learning models using Databricks.
• Deep expertise in feature engineering, feature selection, and feature optimisation.
• Experience building and governing enterprise feature stores.
• Strong knowledge of MLflow for experimentation, model tracking, and governance.
• Experience developing customer propensity, retention, fraud, risk, optimisation, and decisioning models.
• Strong foundation in statistics, machine learning, and decision science methodologies.
• Experience designing model-monitoring frameworks and performance measurement processes.
• Knowledge of Generative AI, prompt engineering, and LLM-based solutions.
• Ability to translate business challenges into scalable analytical solutions and measurable outcomes.
• Exceptional stakeholder engagement, communication, and influencing skills.
• Proven success delivering end-to-end data science solutions from ideation through production deployment.
• A proactive, self-driven mindset with the ability to thrive in a fast-paced, outcome-focused environment.