SENIOR DATA SCIENTIST - CONTRACT

Indsafri

Sandton

On-site

ZAR 1,200,000 - 1,800,000

Full time

33 hours ago

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Job summary

Indsafri in Sandton, South Africa, seeks an experienced Senior Data Scientist to design, build and optimize machine learning and decisioning solutions across Personal & Private Banking and Digital channels.

You will work with Databricks, MLflow and Delta tables to create customer, risk and operational models, mentor junior data scientists, and produce governance artefacts. This role demands strong Python/SQL, statistical expertise and stakeholder collaboration.

Qualifications

Strong hands-on experience with Databricks Notebooks, Workflows and MLflow.
Experience with Databricks Feature Engineering and Feature Store.
Strong Python and SQL skills.
Strong knowledge of Machine Learning, Statistical Modelling and Feature Engineering.
Experience with Predictive & Prescriptive Analytics.
Experience developing customer decisioning and optimisation models.
Experience working with large-scale customer, behavioural, transactional and digital datasets.
Experience with model validation, monitoring, performance measurement and model governance.
Knowledge of Generative AI, LLMs and prompt engineering.
Ability to translate business problems into analytical solutions and measurable business outcomes.
Strong stakeholder engagement and communication skills.
Proven experience delivering end-to-end Data Science solutions from concept through production.

Responsibilities

Develop, train and optimise machine learning models using Databricks, MLflow and distributed compute environments.
Build customer propensity, next best action, next best product, retention, engagement and customer value models.
Develop risk, collections, fraud and operational models.
Design and maintain reusable feature pipelines using Databricks Feature Engineering and Delta tables.
Define and govern reusable enterprise features within the Databricks Enterprise Feature Store.
Perform feature engineering, feature selection, statistical analysis, experimentation and model validation.
Develop optimisation and decisioning models supporting customer engagement, product recommendations and operational strategies.
Conduct model tuning, calibration, challenger modelling and performance benchmarking.
Monitor model performance, stability, drift and business outcomes.
Develop Generative AI / LLM use cases where applicable.
Work with ML Engineers to productionise models and features.
Produce model documentation, validation reports and governance artefacts.
Mentor junior Data Scientists and contribute to modelling standards and best practices.

Skills

Databricks Notebooks

Databricks Workflows

MLflow

Databricks Feature Engineering

Databricks Feature Store

Delta tables

Python

SQL

Machine Learning

Statistical Modelling

Feature Engineering

Predictive Analytics

Prescriptive Analytics

Customer decisioning

Generative AI

LLMs

Prompt engineering

Stakeholder engagement

Education

Data Science degree

Computer Science

Mathematical Statistics

Actuarial Science

Mathematics

Econometrics

Master’s or Doctorate

Tools

Databricks Notebooks

Databricks Workflows

MLflow

Databricks Feature Engineering

Databricks Feature Store

Delta tables

Job description

We are looking for an experienced Senior Data Scientist to join a high-impact data and analytics environment, supporting Personal & Private Banking (PPB) and Digital channels.

The successful candidate will design, develop and optimise machine learning, AI and decisioning solutions that drive customer, risk and operational outcomes.

Key Responsibilities

Develop, train and optimise machine learning models using Databricks, MLflow and distributed compute environments.
Build customer propensity, next best action, next best product, retention, engagement and customer value models.
Develop risk, collections, fraud and operational models.
Design and maintain reusable feature pipelines using Databricks Feature Engineering and Delta tables.
Define and govern reusable enterprise features within the Databricks Enterprise Feature Store.
Perform feature engineering, feature selection, statistical analysis, experimentation and model validation.
Develop optimisation and decisioning models supporting customer engagement, product recommendations and operational strategies.
Conduct model tuning, calibration, challenger modelling and performance benchmarking.
Monitor model performance, stability, drift and business outcomes.
Develop Generative AI / LLM use cases where applicable.
Work with ML Engineers to productionise models and features.
Produce model documentation, validation reports and governance artefacts.
Mentor junior Data Scientists and contribute to modelling standards and best practices.

Key Skills & Experience

Strong hands-on experience with Databricks Notebooks, Workflows and MLflow.
Experience with Databricks Feature Engineering and Feature Store.
Strong Python and SQL skills.
Strong knowledge of Machine Learning, Statistical Modelling and Feature Engineering.
Experience with Predictive & Prescriptive Analytics.
Experience developing customer decisioning and optimisation models.
Experience working with large-scale customer, behavioural, transactional and digital datasets.
Experience with model validation, monitoring, performance measurement and model governance.
Knowledge of Generative AI, LLMs and prompt engineering.
Ability to translate business problems into analytical solutions and measurable business outcomes.
Strong stakeholder engagement and communication skills.
Proven experience delivering end-to-end Data Science solutions from concept through production.