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.
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