Senior Data Scientist

A new vacancy is available for a Senior Data Scientist in a hands-on role involving designing machine learning solutions, conducting statistical analyses, and uncovering actionable insights that directly impact decision-making.

About the Team & Role:

Our client’s mission is supported by a data ecosystem that drives informed decision-making and innovation. The Data Team is critical to this mission, enabling advanced analytics, machine learning, and actionable insights to shape business strategy and outcomes.

This team – comprising data engineers, data scientists, and data analysts – works collaboratively to transform raw data into impactful solutions, ensuring scalability, reliability, and actionable insights.

As a Senior Data Scientist, you will play an integral role in solving complex analytical challenges and deploying predictive models that support strategic goals. You'll take ownership of the data science project results while guiding and supporting junior team members and stakeholders throughout the journey.

This hands-on role involves designing machine learning solutions, conducting statistical analyses, and uncovering actionable insights that directly impact decision-making. With opportunities to work on embedded and cloud systems, you will tackle projects focused on understanding shopping behaviour and leveraging cutting-edge technology to deliver meaningful business outcomes.

Key Responsibilities:

• Conduct data cleaning and exploratory data analysis (EDA) to uncover patterns, trends, and actionable insights from complex datasets.
• Develop, deploy and monitor machine learning models and algorithms to solve business challenges and enhance operational efficiency.
• Design experiments and statistical tests to validate hypotheses and measure the impact of implemented solutions.
• Knowledge of MLOps and deploying models to production environments.
• Familiarity with version control systems like Git and collaborative workflows.
• Collaborate with data engineers to understand the data architecture and ensure seamless data access, quality, and transformation pipelines.
• Translate business problems into analytical solutions and communicate effectively to non-technical stakeholders.
• Develop and enforce internal data science standards and best practices.
• Stay updated on the latest developments in AI, machine learning, and industry-specific analytics and investigate proof of concept ideas for adoption in the data science team.
• Serve as a technical leader, coach and mentor for junior team members and adjacent data and engineering teams.
• Lead end-to-end data science projects that support strategic goals. This includes requirements gathering, technical deliverable planning, output quality control and stakeholder management.
• Contribute to the development of the data strategy.

Requirements:

• A Bachelor’s degree in Data Science, Computer Science, Mathematics, Engineering or a related field. Advanced degrees are a plus.
• 5 – 8 years of experience as a data scientist, with expertise in machine learning, statistical analysis, and data visualisation.
• Strong proficiency in Python (including libraries like Pandas, NumPy, Scikit-learn, Matplotlib, and TensorFlow/PyTorch) and SQL.
• Strong understanding of data modelling, feature engineering, and model evaluation techniques.
• Experience with experimental design (e.g. A/B testing).
• Experience with data visualisation tools (e.g. Power BI, Tableau) is preferred.
• Familiarity with cloud platforms (e.g. AWS, GCP, Azure) and big data tools (e.g. Spark, Databricks).
• Experience leading and mentoring junior data scientists and other team members
• Experience contributing to and shaping internal data science standards and best practices.
• Strong problem-solving and critical thinking skills and the ability to work with cross-functional teams to deliver results.
• An innovative, collaborative mindset with excellent communication skills to work across teams.

Bonus Points & Other Considerations:

• Experience working in the retail or consumer analytics industry.
• Hands-on experience with computer vision, natural language processing, or mathematical optimisation.
• Contributions to open-source projects; research papers or personal projects in relevant fields.
• Certifications in data science, machine learning, or cloud technologies (e.g. AWS Certified Machine Learning, Databricks).

Benefits

• Competitive base salary
• Bi-Annual Key Performance Objectives (KPO) Bonus Scheme
• Employer-sponsored provident fund (% of base salary will be discussed)
• Employer-sponsored Discovery health plan (% of base salary will be discussed)
• Hours and place of work are determined by operational requirements (currently remote).