Senior Data Scientist
Location:
- Remote - UK/Germany/Spain/Ireland/Poland/Netherlands/Lithuania/Bulgaria
- From Home / Beach / Mountain / Cafe / Anywhere!
- We are a remote-first company with a globally distributed team. You can find your productive zone and work from there.
Location
- Remote - USA or Canada
- From Home / Beach / Mountain / Cafe / Anywhere!
We are a remote-first company with a globally distributed team. So you can find your productive zone and work from there.
About the role
We're looking for a data-driven professional to help us measure, understand, and improve the performance of our risk strategies — and to stay ahead of evolving fraud threats by designing and deploying data-driven solutions with real-world impact. You'll work directly with clients to understand their unique fraud challenges, rapidly prototype proof-of-concept models, and build scalable, production-ready solutions using machine learning and graph analytics. You'll also analyze complex datasets, design metrics, build dashboards, and collaborate closely with stakeholders across the business to drive decision-making and optimize outcomes.
This is a hands-on, high-impact role ideal for someone who thrives at the intersection of data science, client-facing problem solving, and real-time risk.
What you'll be doing
- Champion a data-first approach across internal teams and client engagements, promoting clarity and impact
- Build and deploy machine learning models to prevent fraud across diverse fintech use cases, from proof-of-concept through to production
- Develop and track metrics to measure and monitor the performance of our risk products and the effectiveness of risk management strategies
- Conduct in-depth analyses to uncover insights contributing to fraud reduction and higher approval rates for our clients
- Work directly with clients to understand their fraud challenges and translate complex data insights into clear, actionable recommendations
- Use data and models to support the development of risk mitigation strategies and interventions while preserving and improving the user experience
- Create and automate self-serve dashboards leveraging BI tools
- Collaborate with engineering to scale models into production, optimize performance, and support data instrumentation
- Partner with cross-functional teams (Business, Product, and Engineering) to translate business requirements into data-driven solutions
What you'll need
- 7+ years of experience in data science, quantitative modeling, or a data-focused role (product analytics, business analytics) with demonstrated high impact in fraud or risk contexts
- Strong hands-on experience with Python/R and SQL is essential, with Spark being a nice to have
- Expertise in BI tools such as Tableau, Sigma, or Metabase
- Proven ability to structure and analyze complex data using techniques like EDA and cohort analysis, and communicate findings effectively to both technical and non-technical audiences, including clients
- Sharp critical thinking and creative problem-solving skills with a bias toward action
- Proficiency in defining, tracking, and communicating performance metrics