Senior Data Scientist

YouLend; Camden Town; Hybrid; GBP 80,000 - 100,000; Full time

Benefits offered by this job

Private Medical Insurance (via Vitalty

EAP with Health Assured

Enhanced Maternity and Paternity Leave

Great office space in Central London

Subsidised lunch

Deliveroo allowance

Monthly in-office masseuse

Team and Company socials

Sports clubs

Job summary

YouLend in London is seeking a Senior Data Scientist to join the Credit Risk team. This hybrid role will be based at our London headquarters, applying advanced analytics and machine learning to shape embedded finance.

You will develop and refine Probability-of-Default and Revenue-Forecasting models while transforming data-driven insights into business decisions. Collaborating with cross-functional teams, you will ensure robust data pipelines and contribute to the model lifecycle and MLOps

Qualifications

• Experience as a data scientist in fintech.
• Proficiency in Python and SQL for data manipulation and modeling.
• Hands-on experience with a range of ML algorithms and MLOps practices.
• Ability to translate data into actionable insights for technical and non-technical audiences.
• Experience with financial/transactional datasets is a plus.

Responsibilities

• Analyse large datasets to uncover patterns informing business decisions.
• Build and deploy ML models to forecast outcomes and detect fraud.
• Develop algorithms for pricing or risk assessment.
• Create visualisations and dashboards to communicate findings to stakeholders.
• Collaborate with risk managers, engineers, and commercial teams to integrate insights.
• Partner with data/ML engineering to ensure robust data pipelines.
• Contribute to MLOps and model lifecycle best practices.

Skills

Python

SQL

ML algorithms

MLOps

Data visualization

Stakeholder communication

Fintech domain knowledge

Job description

Senior Data Scientist

Department: Credit Risk

Employment Type: Permanent

Location: London

Reporting To: Yury Trostin

Compensation: £80,000 - £100,000 / year

Description

We’re looking for a Senior Data Scientist to join our growing Risk team. This hybrid role will be based in our London headquarters from where we support all our global businesses. Leveraging advanced analytics and machine learning, you’ll play a pivotal role in shaping the future of embedded finance. From developing and enhancing Probability-of-Default and Revenue-Forecasting models to uncovering insights that drive smarter decisions, your work will directly impact how businesses access finance and serve their customers better. You’ll work closely with cross-functional teams to integrate data-driven solutions into our products and strategies, helping businesses access finance and serve their customers better.

Key Responsibilities

• Analyse large, complex datasets to uncover patterns, insights, and trends that inform business decisions.
• Build and deploy machine learning models to forecast financial outcomes, detect fraud, optimise credit risk, and enhance customer personalisation.
• Develop and improve algorithms for financial services such as pricing or risk assessment.
• Create compelling visualisations and dashboards to communicate findings to stakeholders.
• Collaborate with risk managers, engineers, and commercial teams to integrate data-driven insights into our products and strategies.
• Partner with the data and ML engineering team to ensure data pipelines are robust, scalable, and optimised for analysis and inference.
• Contribute to best practices in MLOps and model lifecycle management.

Skills, Knowledge & Expertise

• Proven experience as a data scientist within a fintech.
• Strong proficiency in Python and SQL for data manipulation, analysis, and model development.
• Hands‑on experience with a wide range of machine learning algorithms and foundational MLOps practices.
• Ability to design and build predictive models that solve real business problems.
• Skilled at translating complex data into clear, actionable insights for technical and non‑technical audiences.
• Experience working with financial or transactional datasets is a plus.

Job Benefits

Why join YouLend?

• Award-Winning Workplace: YouLend has been recognised as one of the “Best Places to Work in 2024, 2025 and 2026” by the Sunday Times for being a supportive, diverse, and rewarding workplace.
• Award-Winning Fintech: YouLend has been recognised as a “Top 250 Fintech Worldwide” company by CNBC.

It's just getting fun

• We have developed powerful solutions, secured significant partnerships, and are growing rapidly.
• The global opportunity is still massive, and YouLend is a raw organisation where we are only just getting started.

Lots of upsides

• High-growth (>100% growth during 2022 and 2023), so clear outlook to compensation (bonus or share option appreciation) and career growth (through growth with the business).
• Well-capitalised with supportive private equity backing.
• Part of Banking Circle Group with a fully licensed Luxembourg bank, which can provide a balance sheet and support European expansion in otherwise complex regulated markets.

Motivating work environment

• A high-quality team that pushes each other to succeed through direct feedback and aligned incentives.
• Strong, transparent team culture: we have each other’s backs.
• Independent work environment where results matter.
• Data‑driven culture and emphasis on speed (anti-red tape).

We offer a comprehensive benefits package that includes:

• Private Medical Insurance (via Vitality)
• EAP with Health Assured
• Enhanced Maternity and Paternity Leave
• Great office space (including a gym!) in Central London
• Subsidised lunch (via Feedr)
• Deliveroo allowance if working late in the office
• Monthly in‑office masseuse
• Team and Company socials
• Sports clubs

At YouLend, we champion diversity and embrace equal opportunity employment practices. Our hiring, transfer, and promotion decisions are exclusively based on qualifications, merit, and business requirements, free from any discrimination based on race, gender, age, disability, religion, nationality, or any other protected basis under applicable law.