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

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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.

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Data Scientist

Job Description