Data Scientist (Intermediate)

Discovery Limited; Gauteng; On-site; ZAR 600 000 - 800 000; Full time

Job summary

A leading company is seeking an Intermediate Data Scientist to join their expanding Data Science Lab. The role involves developing algorithms to improve health outcomes and user engagement, analyzing diverse data, and collaborating with teams to optimize digital solutions. Ideal candidates will have a strong background in data science, proven analytical skills, and a passion for healthcare innovation.

Qualifications

• Proven experience in analytics and machine learning model implementation.
• 2-5 years of relevant experience is advantageous.

Responsibilities

• Develop personalized models to foster healthy habits and enhance user engagement.
• Collaborate with cross-functional teams to integrate data science pipelines.

Skills

Creativity

Communication

Analytical Thinking

Time Management

Education

Honours, Master's, or PhD in Data Science

Actuarial Science

Statistics

Computer Science

Applied Mathematics

Tools

Python

R

SQL

Microsoft Office

Job description

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Data Scientist (Intermediate)

Business Unit : Discovery Health

Function : Data Sciences

Date : 30 Apr

About Discovery

Discovery's core purpose is to make people healthier and to enhance and protect their lives.

We seek out and invest in exceptional individuals who understand and support our core purpose, and whose own values align with those of Discovery.

Our fast-paced and dynamic environment enables smart, self-driven people to be their best.

As global thought leaders, Discovery is passionate about innovating to achieve financial success and to ignite positive and meaningful change within society.

About (Data Science Lab)

The Group Data Science Lab (DS Lab) is expanding, and we're looking for talented individuals to join our growing team.

Our global team collaborates with partners such as Discovery Health Digital, Quantium, Risk Intelligence, and renowned institutions like the London School of Economics (LSE).

We work across diverse areas—including digital, clinical, wellness, and behavioral themes—using a modern big data architecture to harness terabytes of structured and unstructured data.

The DS Lab adopts a forward-thinking approach, identifying new data sources and opportunities, and leveraging the Vit.AI platform to create scalable, fit-for-purpose solutions that serve the business into the future.

Key purpose

The Data Science Lab is dedicated to creating impactful, long-lasting solutions to meet essential business needs. Our primary objectives include:

1. Developing personalized models and algorithms to foster healthy habits, achieve positive health outcomes, and enhance user engagement with Discovery products and services.
2. Optimizing customer communication through our extensive data assets.
3. Employing Large Language Models (LLMs) to improve our servicing and coaching capabilities.
4. Fostering a culture of experimentation via a test-learn-adapt approach for continual improvement and innovation.

Data analysis and modelling

• Extracting and analyzing digital, clinical, and behavioral data to inform product design and customer experience strategies for digital solutions.
• Developing data science models and A/B testing pipelines for deployment.
• Applying statistical techniques, behavioral science principles, and data science models to measure and optimize member engagement and user experiences.

Collaboration with Cross-functional Teams

Work closely with Discovery Health Digital to align insights and modelling inputs with product objectives and app engagement outcomes. Collaborate with systems and engineering teams to integrate data science pipelines into health systems and digital solutions.

Reporting and Insights

Present insights and results to stakeholders and senior executives, emphasizing the impact of personalized digital experiences on user engagement and satisfaction.

Personal Attributes and Skills

• A creative, enthusiastic attitude towards uncovering insights and generating value.
• Ability to manage multiple priorities and understand how analytics fit into the broader business context.
• Results-driven, curious, and capable of working autonomously or in teams.
• Good time and task management skills.
• Effective communication of analysis results.
• Aligned with Discovery values and core purpose.

Experience, qualifications, and mandatory requirements

• Honours, Master's, or PhD in Data Science, Actuarial Science, Statistics, Operations Research, Computer Science, or Applied Mathematics.
• Ability to formulate clear problem statements, develop plans, and communicate findings effectively.
• Proven experience in analytics, focusing on building and implementing machine learning models for business problems.
• Experience with data access and analysis using Python, R, SQL, etc.
• Experience with Gradient Boosting Machines, Random Forests, Neural Networks, or similar algorithms.
• Good knowledge of Microsoft Office tools.
• Desirable: Experience with big data tools and working with large, disparate datasets.
• A strong interest in healthcare, behavioral science, and risk management in the healthcare sector.
• 2-5 years of relevant experience is advantageous but not required.

EMPLOYMENT EQUITY: The company's Employment Equity Plan and Targets will be considered during recruitment. We encourage applications from people with disabilities as part of our commitment to equal opportunity employment.