Data Scientist

We're looking for a Data Scientist to join NewDay, focused on uncovering new insights from complex data and developing models that drive value for both the business and our customers.

Sitting within a regulated credit environment, this role spans the full data science lifecycle, from exploring and shaping new data sources, through to building, governing, and monitoring models in production. You'll work closely with senior stakeholders and partner teams to ensure outputs are robust, well-governed, and clearly communicated.

This is a hands-on role for someone passionate about applied modelling, data exploration, and turning advanced analytics into practical, real-world outcomes.

How you'll contribute

• Use sophisticated statistical and machine learning techniques to identify new trends and relationships in data.
• Harvest, wrangle and prototype new data sources internally and external to NewDay to create new value for NewDay and our customers.
• Provide quality and detailed data science outputs, sharing and following up with as much detail as appropriate or requested by senior managers.
• Develop knowledge of all relevant data resources within NewDay and in the wider Credit Industry.
• Governance: support the models throughout their lifecycle from conception, development, implementation, testing and monitoring, with the required level of documentation to follow internal procedures and standards.

• Degree (BSc or higher) in a data science-related field (e.g. statistics, mathematics, machine learning)
• Strong experience with statistical modelling and machine learning techniques
• Proficiency in Python, including libraries such as pandas, numpy, scikit-learn
• Solid SQL and data manipulation skills, including cleaning and managing raw datasets
• Experience with data visualisation and communicating insights clearly
• Strong analytical and problem-solving skills

It's a plus if you also have these skills

• MSc or PhD in a data science-related discipline
• Experience within a regulated financial services environment
• Ability to present complex findings clearly to varied audiences
• Experience supporting model deployment and working with implementation or DevOps teams