Data Scientist (Behavioural)

Our Behavioural Innovation and Research team is seeking exceptional individuals with strong expertise in data science, analysis, modelling, and statistics, who are interested in applied behavioural science. In particular we’re seeking an individual who can drive research and data analysis into technology design and implementation, helping turn our innovation into practical technologies, and bridging the gap between our research team and our technology and product teams. For this, experience and ability with Python is essential, and experience with APIs, NoSQL, QuickSight or Tableau, R and cloud computing are desirable.

• Contribute as key member of the Behavioural Innovation and Research team, reporting to the Head of Innovation
• Develop behavioural technology to guide people towards better financial decisions, with a focus on hyper-personalised investor communication and engagement 
• Work closely with the head of product and the development team to make sure we build the right things in the right way 
• Work alongside the sales team and marketing team to explain our products to prospects and customers, and ensure we design solutions to meet our clients’ needs

Required skills and experience  

• Experience working in a data science context, typically with a Master’s degree in a related field. This may be from a behavioural/decision science degree with strong quantitative/data components.
• Strong quantitative, modelling, analysis, and statistical skills; good knowledge of statistical and programming packages (particularly Python)
• Experience in taking analysis and insight into in designing practical tools and products to assist decision making (e.g. use of Figma type tools to take conceptual innovation to practical design)

Required attributes

• Curiosity and interest in applied behavioural/data/decision science
• Ability to effectively communicate complex ideas to a wide range of audiences
• Highly organised, thorough, details-oriented, and able to document and track data with clarity
• Proactive, collaborative, and able to operate independently

Good-to-have skills and experience  

• Expertise in data engineering, machine learning, and artificial intelligence techniques, especially recommendation systems
• Familiarity with one or more of:
  • Behavioural finance/economics and/or decision science
  • Finance: theory, risk, financial advice, wealth management, investment suitability, sustainable finance/investing, or financial wellbeing
  • Psychometrics, survey design, and data visualisation
• Product and consumer interface design, behavioural UX/UI, Figma, data visualisation
• Experience with consulting, and client and project management

We do not expect applicants to have equally strong expertise in all the above areas: they will all be covered across the team, and we are looking for individuals who are interested in using a broad range of skills to deliver practical solutions.

You are more fox than hedgehog.

Oxford Risk has a vision for improving financial wellbeing and helping people make the best decisions to support their life choices. We understand financial decisions are complex and daunting, and we all have anxieties and biases that can get in the way of good outcomes. We’re here to fix that.

We are a small, innovative team with big ambitions. We combine data research, behavioural science, and quantitative finance expertise to develop user-friendly products that support holistic financial decision-making — spanning investment, savings and borrowing. Our technology empowers financial service providers, from fintechs to banks, provide hyper-personalised advice to their clients, for today and for a lifetime of financial decisions.

Why join us now?

After a period of rapid growth, we’re building our team to expand into new markets, enhance our product offering, and develop new products, including an increasing focus on sustainable investing, financial wellbeing, and hyper-personalised behavioural client engagement. There are exciting opportunities to explore the potential for machine learning, and the use of behavioural nudging to improve customers’ ability to stick to their plans and reach their financial goals.