Senior Data Scientist

Who Are We?

Sanlam Life and Savings (SLS) is focused on serving our retail and corporate clients in South Africa and further developing our strategic advantages in the South African market. Sanlam Life and Savings consists of the following business units Retail Mass, Corporate, Risk and Savings, Glacier and various business enabling functions. The Sanlam Life and Savings Office provides strategic direction, coordination and support to the four clusters, as well as performing governance oversight that includes assurance provided by second line of defense functions in SLS, to enable us to meet our business objectives.

Role Description

As a Senior Data Scientist, you will be positioned within the AI Solutions team, a group at the forefront of generating data-driven strategies to improve decision-making within the Sanlam Life & Savings Cluster, with opportunities to extend your impact across the broader organization.

You will lead the design, development, and deployment of advanced data science solutions that solve real-world business problems and deliver measurable business value. From predictive modelling and statistical inference to machine learning and generative AI, you will drive end-to-end projects that demonstrate clear outcomes.

Working closely with cross-functional teams, including Data Engineers, AI Solutions Engineers, product owners, and business stakeholders. In essence, you will turn complex data into actionable insights, shape data science solution approaches, and contribute to maturing our data science value-add.

This role also encompasses a leadership component with an expectation to mentor and guide junior team members, helping to grow technical capability and foster a culture of experimentation and continuous learning.

What Will You Do?

Key Responsibilities

• Lead the development of advanced analytical models and algorithms to address business challenges and opportunities.
• Translate complex business problems into data science projects with clear objectives, hypotheses, and success criteria.
• Apply statistical modelling, machine learning, deep learning, and NLP techniques to unlock value from structured and unstructured data.
• Collaborate with data engineering and MLOps teams to ensure robust data pipelines and production-ready deployment of models.
• Design and run experiments to validate models, evaluate performance, and guide decision-making through data.
• Lead and manage end-to-end delivery of data science projects, ensuring alignment with business goals, timelines, and quality standards.
• Quantify the business value and impact of data science solutions, supporting ROI tracking and performance measurement of deployed models.
• Communicate findings and recommendations to both technical and non-technical stakeholders in a clear, impactful manner.
• Contribute to the design and implementation of reusable data science assets, frameworks, and best practices.
• Mentor and develop junior data scientists and analysts, creating growth opportunities, sharing technical expertise, and instilling a culture of curiosity, experimentation, and continuous learning.
• Stay current with the latest developments in data science, AI, and technology to drive innovation in the team’s capabilities.
• Promote ethical AI practices, data governance, and model transparency throughout the solution lifecycle.

What Will Make You Successful In This Role?

Requirements

Technical Expertise:

• Proven experience in developing and deploying machine learning and statistical models in production environments.
• Strong programming skills in Python or R.
• Solid grounding in statistics, linear algebra, and probability theory.
• Experience with working on large, complex datasets, both structured and unstructured.
• Skilled in data wrangling, feature engineering, and model tuning.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and modern data ecosystems (e.g., Spark, Databricks, Snowflake).
• Familiarity with ML Ops workflows, version control (Git), and collaboration tools.
• Demonstrated ability to drive innovation by exploring novel algorithms, new modelling techniques, and emerging technologies (e.g., Generative AI, foundation models).
• Strong capability to lead technical discussions, influence architectural decisions, and mentor junior data scientists.
• Understanding of responsible AI, model interpretability, and bias mitigation.

Education & Certifications:

• Preferred: Master’s degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field.
• A Bachelor’s degree combined with significant relevant experience will also be considered.
• Certifications in machine learning (e.g. TensorFlow Developer), cloud platforms (e.g., AWS Machine Learning Specialty, or Microsoft Azure Data Scientist), or advanced analytics tools are advantageous.

Collaboration & Communication:

• Strong project management skills with the ability to scope work, manage timelines, and communicate progress to stakeholders.
• Ability to define and track success metrics that demonstrate the business value of AI and analytics initiatives.
• Ability to collaborate effectively with cross-functional teams, including business, engineering, and product stakeholders.
• Strong data storytelling and visualization skills (e.g., using Power BI, Tableau, or custom Python visualization libraries).
• Experience operating in agile delivery environments.

Personal Attributes:

• Insightful – You bring clarity to complexity and help teams see opportunities in data.
• Strategic – You align your work with business priorities and think beyond the model.
• Innovative – You continuously seek new approaches to push the boundaries of what data science can do for the business.
• Leadership-Oriented – You actively support the development of others and take initiative in shaping strategy and team capability.
• Analytical – You approach problems methodically and base decisions on evidence.
• Collaborative – You work well across disciplines and support a shared vision.
• Curiosity – You stay ahead of the curve by exploring new tools, methods, and trends.

Build A Successful Career With Us

We’re all about building strong, lasting relationships with our employees. We know that you have hopes for your future – your career, your personal development and of achieving great things. We pride ourselves in helping  our employees to realise their worth. Through its five business clusters – Sanlam Fintech, Sanlam Life and Savings, Sanlam Investment Group, Sanlam Allianz, Santam, as well as MiWay and the Group Office – the group provides many opportunities for growth and development.

Core Competencies

Cultivates innovation - Contributing through othersCustomer focus - Contributing through othersDrives results - Contributing through othersCollaborates - Contributing through othersBeing resilient - Contributing through others

Turnaround Time

The shortlisting process will only start once the application due date has been reached. The time taken to complete this process will depend on how far you progress and the availability of managers.

Closing date: 13 October 2025

Our Commitment To Transformation

The Sanlam Group is committed to achieving transformation and embraces diversity.  This commitment is what drives us to achieve a diverse, inclusive and equitable workplace as we believe that these are key components to ensuring a thriving and sustainable business in South Africa.  The Group's Employment Equity plan and targets will be considered as part of the selection process.