At a Glance
- Tasks: Lead the development of credit risk models and turn data into actionable insights.
- Company: Wayflyer, a fast-growing fintech empowering SMBs with quick financing solutions.
- Benefits: 25 days paid leave, private healthcare, equity scheme, and remote work options.
- Other info: Collaborative culture with opportunities for career growth and mentorship.
- Why this job: Join a dynamic team and make a real impact on global funding operations.
- Qualifications: 4+ years in Data Science/ML with strong coding skills in Python and SQL.
The predicted salary is between 43200 - 72000 € per year.
Company Mission
Our mission is to give the world access to the best products by empowering great businesses to reach their growth potential.
About Wayflyer
Today's SMBs need a capital provider that keeps pace with their growth ambitions. Traditional financing options are slow, cumbersome and often out of reach. That’s why we built Wayflyer. Our unique technology allows us to assess businesses in minutes, generate financing offers that reflect their growth potential and send funds in as little as 24 hours. Since launching in April 2020, we’ve deployed over $5bn to thousands of businesses worldwide, backed by Tier 1 banks like J.P. Morgan. We’ve become a trusted financing partner for some amazing brands.
Culture & Values at Wayflyer
At Wayflyer, we value being sound people, excellent operators, and ambitious overachievers, working together with integrity, creativity, and bold optimism to deliver exceptional results.
Your Role at a Glance
The key ways you’ll bring value to the team:
- Production-Grade ML Engineering: Lead the end-to-end lifecycle of credit risk models, treating Machine Learning as a branch of software engineering to ensure all outputs are fast, reproducible, and robust.
- Strategic Risk Modelling: Design and implement sophisticated modeling frameworks (such as decisioning, pricing or fraud methodologies) that move the needle on company-wide P&L.
- Credit Strategy & Optimisation: Develop data-driven credit policies and lending strategies that safely expand our addressable market, driving higher conversion and maximising our growth and profitability.
- Statistical Rigour: Serve as a guardian of scientific integrity, ensuring that model improvements are statistically significant and free from data leakage or bias.
- Commercial Influence: Translate technical findings into "Business Trade-offs" for leadership, mapping model performance directly to revenue and loss metrics.
- Technical Stewardship: Set the standard for code quality within the team by performing high-value code reviews, mentoring junior team members, and contributing to core internal libraries.
What Makes You a Great Fit
- Experience: 4+ years in Data Science/ML, with a proven track record of building and maintaining production-grade ML systems.
- Statistical & Modeling Depth: Advanced knowledge of predictive modeling and credit risk concepts.
- Engineering Excellence: Advanced proficiency in Python and SQL.
- AI Native: Ability to leverage AI and LLMs as accelerants for high-quality output.
- Domain Expertise: Deep understanding of credit risk metrics and the trade-offs between risk appetite and growth.
- Communication Skills: The ability to persuade non-technical stakeholders and distill high-level risk strategy into a clear, actionable story.
How You’ll Stand Out
- Experience in highly automated lending and portfolio optimisation.
- Experience in price setting and modelling price sensitivity.
- Experience in modelling Customer Lifetime Value (CLV).
What to Expect After You Apply
You can expect to hear from a member of our Talent Acquisition team soon. If we believe you’re a good fit, the first step will be a conversation with a recruiter who will guide you through the next stages of the process.
The Perks of Being at Wayflyer
- Time Off That Matters: Recharge with 25 days of paid annual leave, plus public holidays.
- Your Wellbeing: Access support and resources to support your wellbeing.
- Comprehensive Health & Protection: Stay covered with private healthcare, life insurance, and critical illness cover.
- Secure Your Future with Our Pension Plan: Our pension plan helps you build a strong foundation for tomorrow, starting today.
- Family-First Policies: We provide a generous parental and adoptive leave program for both Primary and Secondary caregivers.
- Share in Our Success: With our equity scheme, you’re not just an employee; you’re a stakeholder in our journey.
- Work From Abroad!: Enjoy the freedom to work remotely from anywhere in the world for up to 60 calendar days a year.
Global Offices and Working Policy
Dublin, London, Sydney, Charlotte, and remote opportunities across the US & Europe.
How We Handle Your Personal Data
By submitting your application, you acknowledge that Wayflyer Limited will process your personal data for the purpose of evaluating your suitability for the role.
Senior Credit Risk Data Scientist in London employer: Wayflyer
Wayflyer is an exceptional employer that champions a culture of collaboration and innovation, making it an ideal place for a Senior Credit Risk Data Scientist to thrive. With a commitment to employee wellbeing, generous leave policies, and opportunities for professional growth, Wayflyer empowers its team members to make impactful contributions while enjoying the flexibility of hybrid work arrangements from vibrant locations like Dublin and London. Join us to be part of a dynamic team that values integrity, creativity, and ambition, all while sharing in the success of our mission to support businesses worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Credit Risk Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to current employees at Wayflyer on LinkedIn or through mutual connections. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Prepare for the interview by brushing up on your technical skills. Make sure you can discuss your experience with predictive modelling and credit risk concepts confidently. We want to see how you can turn data into dollars!
✨Tip Number 3
Show off your communication skills! Be ready to explain complex statistical theories in simple terms. Remember, it’s all about translating those technical findings into actionable insights for the team.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Wayflyer family.
We think you need these skills to ace Senior Credit Risk Data Scientist in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Credit Risk Data Scientist role. Highlight your experience in data science and machine learning, especially any projects that relate to credit risk. We want to see how your skills align with our mission!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you're passionate about credit risk and how you can contribute to Wayflyer's growth. Be sure to mention specific experiences that demonstrate your expertise.
Showcase Your Technical Skills:Since we treat Machine Learning as a branch of software engineering, make sure to highlight your proficiency in Python, SQL, and any relevant tools like Snowflake or dbt. We love seeing examples of production-grade code you've written!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at Wayflyer
✨Know Your Numbers
As a Senior Credit Risk Data Scientist, you'll need to be comfortable with key metrics like PD, EAD, and LGD. Brush up on these concepts and be ready to discuss how they impact credit risk models. Being able to translate these numbers into business outcomes will impress your interviewers.
✨Showcase Your Coding Skills
Since the role involves writing production-grade code, make sure you can demonstrate your proficiency in Python and SQL. Prepare examples of past projects where you've built or maintained ML systems, and be ready to discuss the tools you used, like Snowflake or dbt.
✨Prepare for Technical Questions
Expect to face technical questions that assess your understanding of predictive modelling and statistical rigor. Review common algorithms and their applications in credit risk, and be prepared to explain your thought process when designing models or optimising strategies.
✨Communicate Clearly
You'll need to persuade non-technical stakeholders about complex concepts. Practice distilling your technical findings into clear, actionable insights. Think of examples where you've successfully communicated data-driven strategies to influence decision-making.
