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Senior Data Scientist (JP5860)

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Onsite

Senior Data Scientist (JP5860)

Ovations Talent Sourcing

Senior Data Scientist (JP5860)

Skills

SQL QueriesPythonData ScienceDatabricksMachine LearningAICompliance

2 months ago

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Important information


Contract type:

Freelance / Contract

Location:

Johannesburg, South Africa

Work mode:

Onsite

Published on:

4 September 2026

What they need


Role Overview We are looking for a Senior Data Scientist ,for our client in the banking sector, for a 12-month contract to build and optimize end-to-end machine learning, AI, and decisioning solutions across Personal & Private Banking (PPB) and Digital channels. Leveraging the Databricks platform , you will focus on feature engineering, predictive modelling, experimentation, and decision science to deliver scalable analytical assets.

Key Responsibilities

  • Model Development & GenAI: Design, train, and optimize ML/AI models (customer propensity, next-best-action, risk, fraud, and GenAI use cases) using Databricks and MLflow.
  • Feature Engineering & Governance: Build and maintain reusable enterprise feature pipelines using Databricks Feature Store and Delta tables with full quality and lineage controls.
  • Decisioning & Optimization: Develop decision science models to enhance customer acquisition, engagement, cross-sell strategies, and operational outcomes.
  • Monitoring & Governance: Monitor model performance, stability, and drift; produce complete model documentation and governance artifacts for risk compliance.
  • Stakeholder Collaboration: Partner with PPB, Digital, Risk, and MLOps teams to translate business needs into production-ready analytical solutions.

Minimum Requirements

  • Education: Degree in Data Science, Computer Science, Engineering, Mathematical Statistics, Actuarial Science, Econometrics, or a quantitative field.
  • Databricks Stack: Hands-on experience using Databricks (Notebooks, Workflows, MLflow, and Feature Store/Delta tables).
  • Technical Skills: Strong proficiency in Python and SQL for large-scale data manipulation and machine learning.
  • Domain Modelling: Proven experience building customer (propensity, next-best-action, retention) or operational/risk models in financial services.
  • End-to-End Execution: Demonstrated track record of feature engineering, model tuning, validation, governance, and productionizing models alongside engineering teams.

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