Data Science Manager: Telemetry Solutions

Why Join Us?

This is a rare opportunity to lead at the frontier of actuarial innovation - where data science, machine learning, and software engineering create real-world impact. As Data Science Manager: Telemetry Solutions, you’ll help shape the future of insurance.

• Lead actuarial and data science initiatives across telematics, claims, and operational intelligence.
• Work with rich, real-time datasets from connected vehicles and IoT platforms to unlock insights and build predictive systems.
• Collaborate with cross-functional teams - including product, development, and claims - to integrate analytics into key decision-making processes.
• Apply and grow your technical skills across AI, machine learning, and production-grade systems in a dynamic environment.
• Join a forward-looking team that values innovation, ownership, and continuous learning.

If you're technically strong, strategically curious, and passionate about using data science to tackle bold, modern challenges - this is your opportunity to lead the change.

What will you do?

The Data Science Manager: Telemetry Solutions is a future-focused leadership role that bridges actuarial science, data science, machine learning, and engineering. You will lead a multidisciplinary team that leverages telematics and alternative data to deliver intelligent solutions across usage-based insurance (UBI), claims innovation, product development, and dynamic risk assessment.

This role offers a unique opportunity to operate at the intersection of data, strategy, and technology - driving meaningful transformation in how insurance products are developed, risks are understood, and operations are optimised.

Key Responsibilities:

• Architect and deploy scalable, real-time systems for ingesting, processing, and analysing high-frequency vehicle sensor and telemetry data.
• Develop and maintain robust APIs and automation tools in Python and C# to support internal platforms and customer-facing applications.
• Oversee the creation and deployment of AI models - including computer vision and large language models (LLMs) - to enhance claims automation and document intelligence.
• Champion innovation within the actuarial domain by blending traditional methodologies with modern MLOps, software engineering, and streaming analytics.
• Manage end-to-end machine learning pipelines using tools like MLflow, ensuring reproducibility, governance, and performance monitoring.
• Collaborate closely with Product, IT, Data Engineering, and Claims teams to embed intelligent analytics into core business processes and customer experiences.
• Mentor and grow a high-performing team of data scientists, and software engineers.
• Provide technical insight and data-driven narratives to support strategic decision-making through dashboards, models, and actuarial reporting.

Qualifications

• Degree in Actuarial Science, Data Science, Statistics, Computer Science, or a related field (Honours or Master’s preferred).

Experience

• Minimum of 5 years’ experience in data science, or data engineering roles, preferably in a telematics-driven insurance environment.
• Proficient in Python and C#, with a solid foundation in object-oriented programming and API development.
• Advanced SQL skills, including data processing, database management, and query optimisation (Essential).
• Practical experience using Git for version control and collaboration(Essential).
• Hands-on experience with machine learning libraries and frameworks such as XGBoost, spaCy, Hugging Face, TensorFlow, or PyTorch.
• Proven ability to deploy and monitor models using MLflow and related MLOps tools.
• Experience with large-scale datasets, ideally from IoT or telematics sources.
• Working knowledge of Docker for containerisation (Intermediate to Advanced – Advantageous).
• Exposure to messaging systems such as RabbitMQ (Advantageous).
• Strong understanding of software engineering principles, including object-oriented design and clean code practices.
• Solid business acumen with the ability to translate technical work into strategic outcomes.
• Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Demonstrated leadership experience and a passion for mentoring cross- functional teams.
• Strong analytical and problem-solving skills, with the ability to extract insights from high-volume, high-dimensional data

Knowledge and Skills

Personal Attributes

Core Competencies

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.

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. 

Deadline to apply: 15 May 2025

Our commitment to transformation