Responsibilities
- Develop industry leading data science solutions through:
- Define data requirements and extracting required data to support solution development.
- Perform 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.
- Ensure integrity of the data science solutions in terms of the underlying statistical and economic models and assumptions.
- Collaborate with the MLOps team in the development and deployment of proposed solutions to a live environment and tracking the effects in real time.
- Devise statistically robust testing plans to validate effectiveness of solutions.
- Collate results from in-market tests and validating them.
- Effectively communicate 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.
Requirements
- 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.
- 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.
- 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.
Nice to Have
- 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.
- Ability to create compelling visualisations and dashboards (e.g. Tableau, Thoughtspot).
Benefits
- Competitive pay and benefits, including a performance-based annual bonus, fully subsidised VHI health insurance and pension matching up to 4%.
- Generous time off and flexible working, including 25 days’ annual leave, extra company days, monthly Friday Unplugged afternoons and the option to work abroad for up to 20 days a year.
- Comprehensive wellbeing support, including access to health and mental health programmes (HeadsUp and EAP) and paid leave for marriage, volunteering and personal wellbeing including menstrual, menopause, and fertility leave.
- Growth and recognition culture with development opportunities through training, coaching and study support plus programmes that celebrate individual and team achievements.
- Everyday perks that make a difference - subsidised canteen (KC Peaches), on-site car parking, Bike to Work and TaxSaver schemes plus an active Sports & Social Club.
