Data Scientist

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. 
Reporting to: Head of Data Science

Key Duties & Responsibilities

• 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.
• Devising statistically robust testing plans to validate effectiveness of solutions.
• Collating results from in-market tests and validating them.
• Effectively communicating outputs of work to other team members and business stakeholders in a manner that can be understood by both technical and non-technical audiences.
• Work with colleagues in Revenue function to ensure they are equipped with required tools, models and resources for optimising trading performance.
• Support the wider business with BAU tasks related to the services Data Science provide or with designing new data-driven solutions to solve their complex business problems.
• Proactively work with wider data & technology teams to support the collection of new data and refinement of existing data sources.

Knowledge and Skills:

• 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 communicate complex quantitative analysis in a clear, precise, and actionable manner.
• Proven experience manipulating and analysing complex, high-volume, high-dimensional data from varying sources.
• Ability to create compelling visualisations and dashboards (e.g. Tableau, Thoughtspot).
• Knowledge of Git and modern development workflows.
• Proven ability to work creatively and analytically in a fast-paced, problem-solving environment.
• Ability to partner with Software Engineering teams to co-develop functionality for the business.