Lead Data Scientist - Oakbrook
About Us Formed in 2011, Oakbrook has brought together people with deep expertise in consumer lending, advanced analytics and forward-thinking technologists, with a shared belief that there is a better way to do consumer lending – by being more personalised and customer focused. Our FCA regulated and consumer lending businesses are a leading partner to the aggregator market for consumer loans. Solving the borrowing needs of consumers, and connecting investors and funders seeking to finance consumer assets within their targeted risk-reward parameters. We have a longstanding history of predictable performance for warehouse investors for our on-balance sheet lending, and forward flow lending options for investors and funders seeking to finance consumer assets without specialist consumer credit capabilities. O6K, our business-to-business technology and analytics company, has built our proprietary technology platform from the ground up to support our own lending businesses, but is designed to offer white labelling and platform lending solutions for business partners. Role Summary This role offers an excellent opportunity for a data science professional to develop within a rapidly growing organisation. The data science team is responsible for delivering insight across our marketing, fraud, underwriting, and customer management strategies. The successful candidate will be a key player in this team, providing leadership across a number of different areas. The aim of the position is to advance Oakbrook’s data science and innovation capabilities across the full customer lifecycle including developments within machine learning using innovative data sources not traditionally used by consumer finance companies. Responsibilities
- Owning the development and maintenance of predictive models to improve customer outcomes across fraud, marketing, credit and collections
- Advance our autonomous decisioning capability including model deployment, setting policy, and testing across all areas of the business
- Developing test and learn strategies across different lines of business using data driven analysis, monitoring performance and providing clear recommendations to drive the company forward to help support the company’s ambitious growth aspirations
- Providing leadership and identifying opportunities to improve process and procedures through inquisitive analysis
- Model and Analytical Development:
- Analyse, build and integrate machine learning models that have a tangible benefit to the business
- Deliver valuable insight to the business through thorough analysis and excellent communication
- Quality & Communication:
- Ensure all deliverables are accurate and error-free
- Present findings clearly to technical and non-technical audiences
- Technical Skills
- Experience with the full lifecycle data science projects
- Experienced and knowledgeable in predictive modelling, machine learning and AI
- Good programming skills in R, SQL, Python
- Data visualisation and dashboarding e.g. Power BI
- Understanding of statistical concepts
- Structure thinking and problem-solving capabilities
- Ability to understand IT infrastructure
- Non-Technical Skills
- Commercial acumen
- Usage of Gen AI
- Exceptional Communication and Interpersonal Skills
- Strong time management skills
- Discretion when dealing with confidential information
- Self-motivated and proactive
- Keen eye for detail
- Willingness to adapt role in line with business requirements
- Rule 1: You must act with integrity.
- Rule 2: You must act with due skill, care and diligence.
- Rule 3: You must be open and cooperative with the FCA and other regulators.
- Rule 4: You must pay due regard to the interests of customers and treat them fairly.
- Rule 5: You must observe proper standards of market conduct.
- Rule 6: You must act to deliver good outcomes for retail customers.
- Work with the Best
- Challenge, Grow, Succeed
- Comprehensive Benefits Package
- Generous Holiday Allowance
- Vibrant Office Culture Enjoy free snacks and refreshments in the office, and connect with colleagues at our regular monthly socials.