Senior Data Scientist - Credit Risk

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London, Greater London, England, GBR
In-Office
Fintech • Payments • Financial Services
We’re Teya - proud to serve small, local businesses with the financial tools they need to manage, grow, and thrive.
The Role

Hello! We're Teya.

Teya is a payment and software service provider, headquartered in London serving small, local businesses across Europe. Founded in 2019, we build easy to use, integrated tools that enable our members to accept payments and boost business performance.

At Teya we believe small, local businesses are the lifeblood of our communities.

We’re here because we don’t believe there’s a level playing field that gives small businesses with a fighting chance against the giants of the high street.

We’re here because we see banks and legacy service providers making things harder for them. We don’t think the best technology or the best service should be reserved for those with the biggest headquarters.

We’re here to fight for a future where small, local businesses can thrive, and to commit the same dedication they offer all of us.

Become a part of our story.

We’re looking for exceptional talent to join our mission. We offer a chance to create impact in a high-energy and connected culture, while benefiting from continuous learning opportunities, a supportive community which is proud to serve our mission, and comprehensive benefits.

Your Mission

We’re looking for a Senior Data Scientist to join the Credit team at Teya to drive the development of the credit risk and pricing models that underpin our lending products. This role will play a critical part in delivering our new lending products to small businesses across multiple geographies.

You will lead complex modelling initiatives end-to-end, from problem formulation and data exploration through to deployment in our credit decisioning system and ongoing performance management. You will take ownership of models, developing them to provide a competitive edge through the use of innovative data sources and modelling techniques.

Working closely with Credit Strategy, Product, Engineering and Data Engineering, you will ensure that models are not only statistically sound but also operationally robust and commercially meaningful. Your work will directly influence credit decisions, pricing, and portfolio performance.

This is an excellent opportunity for someone with strong credit modelling skills who wants to make a measurable impact in a fast-growing environment.

Responsibilities

  • Problem solving: Translate credit business problems into modelling and analytics requirements, explore alternative approaches, and define a clear roadmap for delivery.

  • Model development: Lead development of credit risk statistical models and risk-based pricing engines. Present models to non-technical stakeholders, integrate models into the credit decisioning framework, and assess business impact.

  • Model maintenance: Own model performance monitoring, identify weaknesses or drift, and enhance models over time to improve accuracy and reliability.

  • Decisioning framework: Contribute to the design of the overall framework for making credit decisions, incorporating data, models, calculators and rules. Partner with Product, Engineering, Data Engineering and Credit Strategy to bring this into production.

  • Data exploration: Identify and assess new internal and external data sources for use in credit modelling and perform feature discovery and validation.

  • Technical leadership: Contribute to best practices across the model lifecycle, including documentation, testing, and governance, and support the development of junior team members.

Requirements

  • Strong experience in credit risk modelling for SME lending, ideally in a fast-paced environment (fintech, scale-up etc.)

  • Degree in a quantitative field such as Mathematics, Statistics, Engineering or related discipline

  • Excellent applied quantitative skills, including use of machine learning techniques

  • Strong proficiency in Python and SQL

  • Track record in leading activities across the model lifecycle

  • Commercial mindset, with ability to translate models/analysis into actionable recommendations

  • Strong communication skills, comfortable collaborating with multiple functions

Teya is proud to be an equal opportunity employer.

We are committed to creating an inclusive environment where everyone regardless of race, ethnicity, gender identity or expression, sexual orientation, age, disability, religion, or background can thrive and do their best work. We believe that a diverse team leads to better ideas, stronger outcomes, and a more supportive workplace for all.

If you require any reasonable adjustments at any stage of the recruitment process whether for interviews, assessments, or other parts of the application—we encourage you to let us know. We are committed to ensuring that every candidate has a fair and accessible experience with us.

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The Company
HQ: London
1,000 Employees
Year Founded: 2019

What We Do

At Teya, we believe small, local businesses are the heartbeat of every community. Teya was founded to help small, local businesses thrive. We exist to make business smoother, simpler, and more rewarding for the people who keep our communities alive. That means exceptional support, intuitive solutions, and
a team truly invested in our Members’ success.
 To us, they’re more than customers – they’re part of
a community built on trust and shared ambition. 
That’s why we proudly say: “Member since.” 
It’s our way of honouring every relationship and building a stronger, more connected future together.

Why Work With Us

We’re a fast-growing European fintech helping small, local businesses thrive. We value simplicity, teamwork, and impact. At Teya, you’ll join a diverse, passionate team where ideas matter, growth is encouraged, and every action helps real people and communities succeed, every single day.

Teya Offices

OnSite Workspace

We believe great ideas happen when people come together. Our hybrid approach gives you the flexibility to work from home, but we encourage spending at least three days a week in the office to collaborate, connect, and keep our culture strong.

Typical time on-site: None
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