Role Purpose

• Solve complex real-world business problems using cutting-edge machine learning methods and techniques.
• Develop data-driven models and tools to optimise trading performance across a host of domains including pricing and recommended sort.
• Conduct exploratory analysis to generate actionable insights, identify opportunities, and enhance our understanding of consumer behaviours.

Responsibilities & Accountabilities

• Developing industry leading data science solutions through:
• Defining data requirements and extracting required data to support solution development.
• Performing exploratory data analysis to improve understanding of underlying trends and behaviours to help inform feature engineering work and next steps in modelling process.
• Support in the designing and development of scalable and efficient data driven solutions.
• Input into the design decisions determining optimal data science methodologies and technologies to use to solve the problem at hand.
• Ensuring integrity of the data science solutions in terms of the underlying statistical and economic models and assumptions.
• Collaborating with the MLOps team in the development and deployment of proposed solutions to a live environment and tracking the effects in real time.

Skills & Experience Required

• Undergraduate, M.S. or Ph.D. in a relevant quantitative field, and 3+ years’ experience in a relevant role.
• Solid understanding of statistical modelling, algorithms, data mining and machine learning workflows.
• Some experience or knowledge of using more advanced ML libraries (TensorFlow, PyTorch, MXnet, etc.).
• Experience in the development or application of GenAI algorithms seen as a plus.
• Proficient in writing well structured, robust and readable code in Python.
• Proficient in SQL and relevant experience using relational databases.
• Ability to create compelling visualisations and dashboards (e.g. Tableau, Thoughtspot).
• Knowledge of Git and modern development workflows.