Staff Data Scientist β€” Credit Risk & Lending Growth

Staff Data Scientist β€” Credit Risk & Lending Growth

Full-Time 60750 - 74250 Β£ / year (est.) On-site
L

At a Glance

  • Tasks: Lead data science strategy for Credit, shaping underwriting and pricing decisions.
  • Company: Fast-growing fintech company focused on responsible growth.
  • Benefits: Competitive salary, mentorship opportunities, and a dynamic work environment.
  • Other info: Join a team that values experimentation and career development.
  • Why this job: Make a real impact in fintech by driving innovation and responsible decision-making.
  • Qualifications: Experience in data science, predictive modelling, and collaboration skills.

The predicted salary is between 60750 - 74250 Β£ per year.

LemFi is seeking a Senior Data Scientist to lead the data science strategy for Credit, shaping underwriting, pricing, line assignment, fraud/risk interaction, and lifecycle decisioning. You will train and deploy predictive models, monitor performance, and collaborate with product, engineering, analytics, and leadership to ensure responsible growth.

You will drive experimentation, governance, and explainability while mentoring analysts and data scientists in a fast-growing fintech environment.

Staff Data Scientist β€” Credit Risk & Lending Growth employer: LemFi

At LemFi, we pride ourselves on being an exceptional employer that empowers our team to make a real difference in the lives of millions. Our collaborative work culture fosters innovation and growth, providing ample opportunities for professional development while tackling meaningful challenges in the fintech space. Join us in our mission to create a financial ecosystem that supports immigrants and promotes financial inclusion, all while enjoying the benefits of working in a diverse, global environment.

L

Contact Details:

LemFi Recruitment Team

We think you need these skills to ace Staff Data Scientist β€” Credit Risk & Lending Growth

Data Science Strategy
Predictive Modelling
Performance Monitoring
Collaboration
Experimentation
Governance
Explainability