Data Science Manager

📝 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, like True Classic https://wayflyer.com/our-customers/true-classic, Little Words Project https://wayflyer.com/our-customers/little-words-project and Kekoa Foods https://wayflyer.com/our-customers/kekoa-foods. Teams at Wayflyer are truly cross-functional. You'll be collaborating with ambitious colleagues from around the world - all striving to deliver on a huge opportunity. Check out this video https://www.youtube.com/watch?v=J4jcVcdIZ5g&ab_channel=Wayflyer to hear directly from them. 💛 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. To learn more, please visit our website https://wayflyer.com/careers. 🚀 Your Role at a Glance: The key ways you'll bring value to the team As a Data Science Manager at Wayflyer, you will lead a team of 4+ Data Science and ML Engineers. We treat Machine Learning as a branch of software engineering; you will be a hands-on technical leader responsible for writing code, reviewing PRs, and deploying production-grade ML models that powers Wayflyer’s go-to-market and funding processes. - Team Leadership: Manage, mentor, and scale a high-performing team of DS/ML engineers, maintaining a culture of technical excellence and code quality. - Technical Execution: Oversee the end-to-end ML lifecycle: from dataset annotation and model training to deployment, monitoring, and infrastructure maintenance. - Roadmap & Strategy: Partner with Product and Engineering leads to define and execute a data science roadmap aligned with business growth and risk assessment. - Engineering Standards: Implement best practices for reproducible data pipelines, automated testing, and documentation to ensure system reliability. - Stakeholder Management: Translate complex technical findings into actionable insights for VPs and C-suite executives. - AI Native: Ensure the team leverages AI and LLMs as accelerants to producing high quality outputs rather than as a crutch. 🔨 What Makes You a Great Fit - Experience: 5+ years in Data Science/ML, with 2+ years in a formal management or lead role. - Individual Contributor Roots: A proven track record of building and maintaining production ML systems yourself. - Software Engineering: Advanced proficiency in Python and SQL. You should have the core engineering skills required of a Software Engineer. - ML Operations: Practical experience with model deployment, monitoring, and orchestration tools (e.g., Airflow, Dagster). - Product Thinking: Ability to translate business challenges (specifically in risk or growth) into technical data solutions. How You’ll Stand Out - Stack: Python, SQL, Modern Data Stack, Orchestration tools. - Bonus: Experience in FinTech or Credit Risk. - Bonus: Experience with NLP (Text classification, NER). 🤝 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 full interview process, which includes meeting the Hiring Manager and completing a case study or interview loop, typically takes approximately 2-4...