Senior Data Scientist

Tata Consultancy Services; Johannesburg; On-site; ZAR 900,000 - 1,500,000; Full time

Job summary

Tata Consultancy Services (TCS) is seeking a senior data scientist to design and deploy advanced machine learning models using Databricks, MLflow and Delta Lake. The role focuses on customer propensity, risk, fraud, retention and decision strategies across PPB, Digital, Product and Risk teams.

You will productionise models, build reusable features, monitor performance and mentor junior scientists. Strong Python/SQL, statistics, and Generative AI knowledge are essential.

Qualifications

• Advanced degree in a quantitative field is preferred.
• Experience with Databricks MLflow for model tracking.
• Excellent stakeholder engagement and communication.

Responsibilities

• Partner with PPB, Digital, Product and Risk teams to identify high-value analytical opportunities.
• Design, develop, train and optimise ML models using Databricks and distributed compute environments.
• Develop customer propensity, next best action, retention and engagement models.
• Build and maintain reusable feature pipelines and enterprise features.
• Establish feature definitions, quality controls, lineage and monitoring standards.
• Perform model tuning, validation and performance benchmarking.
• Mentor junior Data Scientists and contribute to modelling standards.

Skills

Databricks

Python

SQL

ML & Statistics

Feature Engineering

Generative AI

Stakeholder Management

Experimentation & Validation

Data Visualization

Education

Masters degree or PhD in quantitative field

Tools

Databricks Notebooks

MLflow

Delta Lake

Job description

Tata Consultancy Services (TCS) is an IT services, consulting and business solutions organization that has been partnering with many of the world’s largest businesses in their transformation journeys for over 50 years. TCS offers a consulting-led, cognitive powered, integrated portfolio of business, technology and engineering services and solutions. This is delivered through its unique Location Independent Agile™ delivery model, recognized as a benchmark of excellence in software development.

A part of the Tata group, India's largest multinational business group, TCS has over 616,171 of the world’s best-trained consultants with 157 nationalities in 53 countries. For more information, visit www.tcs.com and follow TCS news at @TCS_News.

Job Description:

Key Responsibilities

• Partner with PPB, Digital, Product and Risk teams to identify and prioritise high-value analytical opportunities.
• Design, develop, train and optimise machine learning models using Databricks, MLflow and distributed compute environments.
• Develop customer propensity, next best action, next best product, customer value, retention and engagement models.
• Develop risk, collections, fraud and operational models to improve business performance and decision quality.
• Build and maintain reusable feature pipelines using Databricks Feature Engineering and Delta tables.
• Define, create and govern reusable enterprise features for inclusion within the Databricks Enterprise Feature Store.
• Establish feature definitions, feature quality controls, lineage and monitoring standards across business domains.
• Perform feature engineering, feature selection and feature importance analysis to improve model performance and reuse.
• Develop optimisation and decisioning models that support customer engagement, product recommendation 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 outcomes and recommend improvements where required.
• Develop Generative AI use cases where appropriate, including customer support, document intelligence and knowledge-based assistants.
• Work closely with ML Engineers to productionise models and features into enterprise platforms and decisioning systems.
• Produce model documentation, validation reports and governance artefacts in line with model risk management requirements.
• Mentor junior Data Scientists and contribute to modelling standards, reusable frameworks and analytical best practices.
• Production-ready machine learning models supporting PPB and Digital use cases.
• Reusable business features deployed within the Databricks Enterprise Feature Store.
• Customer decisioning models supporting acquisition, retention, engagement and cross-sell strategies.
• Risk and operational models supporting improved decision quality and business performance.
• Feature libraries, model documentation and governance artefacts.
• Analytical insights and recommendations delivered to business stakeholders.
• Measurable business value from deployed machine learning and AI solutions.

Key Skills

• Databricks Notebooks, Workflows and MLflow
• Databricks Feature Engineering and Feature Store
• Python and SQL
• Machine Learning and Statistical Modelling
• Predictive and Prescriptive Analytics
• Customer Decisioning and Optimisation
• Experimentation and Model Validation
• Generative AI and LLMs
• Data Visualisation and Storytelling
• Stakeholder Management

Qualifications

Computer Science, Data Science, Engineering, Mathematical Statistics, Actuarial Science, Mathematics, Econometrics or a related quantitative field.

Masters or Doctorate will be an added advantage.

Preferred Certifications

• SAS Data Scientist Certifications
• AWS or Google Cloud AI/ML Certifications
• Machine Learning, Artificial Intelligence or Data Science certifications from recognised providers such as Microsoft, Databricks, SAS, Coursera or DeepLearning.AI

Technical / Professional Knowledge

• Strong experience developing machine learning models on Databricks.
• Strong understanding of feature engineering, feature selection and feature optimisation techniques.
• Experience building and governing reusable enterprise features within Feature Stores.
• Experience using Databricks MLflow for model tracking, experimentation and model governance.
• Experience developing customer propensity, risk, fraud, retention and optimisation models.
• Strong knowledge of statistics, machine learning and decision science methodologies.
• Experience working with large-scale customer, behavioural, transactional and digital datasets.
• Experience designing model monitoring and performance measurement frameworks.
• Knowledge of Generative AI, prompt engineering and applied AI use cases.
• Ability to translate business problems into analytical solutions and measurable business outcomes.
• Strong stakeholder engagement, communication and business consulting skills.
• Experience delivering end-to-end data science use cases from concept through production deployment.
• Self-driven and able to operate effectively in a fast-paced, outcome-focused environment.

Application Deadline: 10-October-2026

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