Jobs Data Science

About Brdge
Brdge is an applied AI consultancy and venture studio. We take world class AI capability and make it usable for the companies that need it most, from the NHS and Home Office to FTSE 100 and Fortune 500 clients, while building our own ventures from zero to one. We move fast and we build real things.

The role
We're looking for a cracked Senior Data Science Analyst who loves to build. Someone who owns problems end to end, sits with clients, untangles the mess, and carries the work all the way to something live.
This is a high intensity environment. We're a small team moving at startup pace, and we want someone who runs at things, takes real ownership, and cares about the work enough to see it through. If you want a predictable nine to five, this isn't it. If you want to build a lot, fast, with people who match your energy, it is.

What we're looking for

• A genuine builder. You'd rather ship a real Django app than polish a deck about one
• Strong traditional ML foundations, and you've gone well beyond them into agentic systems
• A love of pulling apart new architectures and models, the kind who plays with the latest release the weekend it drops
• Solid software engineering and strong Django experience
• AI tooling fluency as a force multiplier, not a crutch
• High ownership, high standards, high pace
• Minimum one year experience. This is about how good you are, not how long you've done it

• London based

   

Hiring fast
We want someone in the next two weeks. If that's you, or someone you rate, apply or get in touch.

Evowill is looking for a Junior Data Scientist who is passionate about data analysis, machine learning, and extracting insights from data, and eager to grow in a supportive and dynamic environment. We offer a clear path: starting with a hands-on internship and transitioning into a commercial project role — 100% of our juniors join real projects.

Requirements:

• Knowledge of Python
• SQL (MySQL / PostgreSQL)
• Basic understanding of Machine Learning (scikit-learn)
• Basic data analysis skills (Pandas, NumPy)
• Solid statistics foundations
• Git, GitHub/GitLab
• English: Intermediate
• Pet projects (data analysis / ML) 
• Fast learner, organized, responsible
  
   

Would be a plus:

• Quantitative Science (Math, physics, statistics) or Engineering with ML or modeling majors (3rd year or higher)
• Experience with statistical or numerical modeling or having participated in data related research teams
  
   

Internship Stage (2 months):

• Full-time, practical learning
• Pet projects, technical interview preparations, and soft skills training
• English Speaking Club
• Senior Developers mentors from Ukraine and Colombia
• Technologies: Core Data Analysis and Modeling, Python libraries, as well as learning to apply modern ML techniques to real-world data.

Project Stage:

• Join commercial projects as a Data Scientist
• Salary from $1000 with regular reviews
• Ongoing mentorship and technical support
• Optional English club and extra tech learning

About RiskSeal

RiskSeal is a B2B startup serving fintech clients globally. Our API-first credit risk management platform enables digital banks and consumer lenders to simplify onboarding through data-driven insights.

We are growing rapidly and value collaboration with passionate, creative professionals. Join us to innovate, contribute your expertise, and grow alongside our team.

Headquarters: Dallas, Texas, USA

European Office: Warsaw, Poland

Job Description

We are looking for a motivated Data Scientist to join our team in a fully remote role. The ideal candidate has experience in credit risk modelling, strong Python and SQL skills, as well as hands-on experience with scoring models. You will build and optimize advanced credit risk and anti-fraud models by leveraging machine learning, anomaly detection, and alternative data alongside traditional scoring. Working with client data, you will translate complex algorithmic outputs into clear, actionable insights for clients, partners, and internal teams.

What we're looking for:

• 2+ years of experience in credit risk modelling.
• Solid knowledge of classical methods (logistic regression, decision trees, scorecards) and ML (boosting, random forests, neural networks).
• Strong Python and SQL skills.
• Background in a bank, fintech, or data vendor environment.
• Experience with PD modelling, scoring, and portfolio performance metrics.
• Comfortable working end-to-end: from raw data to a validated, production-ready output.
• Able to present findings clearly to non-technical audiences, including clients and business partners.
• Upper-Intermediate English level or higher.

What you'll be doing:

• Build, test, validate, and implement predictive credit risk, scoring, and anti-fraud models.
• Analyze complex client data and alternative data streams to uncover hidden insights and deliver data-driven recommendations that guide strategic decisions.
• Continuously monitor and audit model performance (tracking drift, Gini, and PSI) to ensure long-term stability and accuracy.
• Design and experiment with new data attributes, leveraging digital footprint and transactional data to improve model predictability.
• Present analytical findings, model performance reports, and innovative ideas directly to clients, partners, and internal teams.
• Conceptualize new analytical products, scorecards, and advanced data solutions to expand RiskSeal's product offering.
• Partner closely with business, product, and tech teams to deploy models and seamlessly turn data insights into scalable, real-world value.

Nice to Have

• Experience working with alternative data sources.
• Knowledge of model governance and validation frameworks.
• Experience presenting analytical solutions directly to clients.
• Exposure to fintech products, digital lending, or embedded finance.

What We Offer

● A fully remote, full-time role in a growing product fintech company
● A fast-paced environment with minimal bureaucracy and quick decision-making
● The opportunity to work on credit risk models, scoring solutions, and real client data
● Direct collaboration with business, product, and tech teams
● The chance to contribute to analytical products that create real value for clients
● Competitive compensation and opportunities for professional growth