Senior Data Scientist - AI

Indsafri; Sandton; On-site; ZAR 1,000,000 - 1,800,000; Full time

Job summary

Indsafri is seeking a Senior Data Scientist to design, develop, and optimise ML/AI and decisioning solutions across digital and business channels using Databricks.

You will partner with product, digital, and risk teams to identify high-value opportunities, build predictive and prescriptive models, and govern enterprise features within the Databricks Platform. Mentorship and production-ready model delivery are required.

Qualifications

• Strong experience designing, training and validating ML models.
• Proven ability to govern enterprise features in a Feature Store.
• Experience with Databricks MLflow for tracking and governance.

Responsibilities

• Partner with product, digital, and risk teams to identify analytical opportunities.
• Design, train, and optimise ML models using Databricks and distributed compute.
• Build propensity, retention, engagement, fraud, and risk models.
• Develop and govern reusable enterprise features in the Databricks Feature Store.
• Perform feature engineering and model validation; monitor performance.

Skills

Databricks

Notebooks

Workflows

MLflow

Python

SQL

Predictive analytics

Prescriptive analytics

Generative AI

LLMs

Data storytelling

Stakeholder management

Education

Degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, Econometrics, or related quantitative field

Masters or PhD preferred

Tools

Databricks Notebooks

Databricks Workflows

MLflow

Job description

Job Title: Senior Data Scientist - AI & Decision Science

Experience - 5+ Years

Job Purpose

Design, develop, and optimise machine learning, AI, and decisioning solutions that drive customer, risk, and operational outcomes across digital and business channels using the Databricks platform.

Key Responsibilities

• Partner with product, digital, and risk teams to identify high‑value analytical opportunities.
• Design, train, and optimise ML models using Databricks, MLflow, and distributed compute.
• Build customer propensity, retention, engagement, fraud, and risk models.
• Develop and govern reusable enterprise features within the Databricks Feature Store.
• Perform feature engineering, selection, and importance analysis to improve model performance.
• Conduct exploratory data analysis, statistical analysis, hypothesis testing, and model validation.
• Implement model monitoring frameworks for drift, stability, and performance.
• Collaborate with ML Engineers to productionise models into enterprise platforms.
• Produce documentation, validation reports, and governance artefacts.
• Mentor junior Data Scientists and contribute to modelling standards and best practices.
• Production‑ready ML models supporting digital and business use cases.
• Reusable enterprise features deployed in Databricks Feature Store.
• Decisioning models for acquisition, retention, engagement, and cross‑sell.
• Risk and operational models improving decision quality.
• Feature libraries, documentation, and governance artefacts.
• Analytical insights and measurable business value.

Key Skills

• Databricks Notebooks, Workflows, MLflow.
• Python, SQL.
• Predictive & Prescriptive Analytics.
• Generative AI & LLMs.
• Data Visualisation & Storytelling.
• Stakeholder Management.

Qualifications

• Degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, Econometrics, or related quantitative field.
• Masters or PhD preferred.

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.

Company Description-

Indsafri believes in the limitless potential of individuals to create and build anything imaginable. They leverage their deep industry experience and cutting-edge technology to help organizations transform for growth. They work with some of the best organizations around the world and have a global network of partners and talents. Indsafri believes that technology is at its best when it makes people smile. This is a place where with passion and intelligence, anything is possible.