Data Science & Machine Learning Lead, Spade

• 7+ years industry experience, and 2+ years of experience as a data team lead or manager
• A Bachelor’s degree in a relevant field
• Fintech experience, specifically familiarity with payments-related data (e.g., card, debit, acquirer, and/or merchant data) and / or transaction data (e.g., card ard authorization and fraud prevention)
• Deep experience in machine learning and statistical algorithms and techniques related to entity resolution, such as probabilistic linking, deep learning models, embeddings, and clustering models
• Ability to create compelling narratives with data that translate complex technical concepts and findings to non-technical stakeholders, employing data science tools and visualization techniques such as Python, querying languages (SQL), and plotting libraries (Matplotlib, Plotly) where relevant
• Strong problem-solving skills and ability to guide team in breaking down complex product and technical challenges into accurately estimated milestones
• A desire to focus on customer needs and solve pressing problems

Desirable

• As the founding data leader at Spade, you will have the opportunity to get hands-on experience working on green-field data projects, play a key role in developing our product, and lay the foundation for our growing data science team
• Lead our data function, collaborating closely with our CTO, CEO, and Engineering Manager on long-term product and data strategy, while running the planning process and managing a team to execute on short term objectives
• Manage and mentor a team of incredible data scientists, building a high-performing, inclusive, and empathetic culture
• Work with your team to build top-tier merchant databases and low-latency APIs, leveraging techniques such as large-scale entity resolution models, including probabilistic models, embeddings, and clustering models
• Swiftly ship high-impact and scalable data products that enhance Spade’s customer experience, by collaborating closely with technical and non-technical functions, and finding the right balance between theoretical soundness and practicality
• Use your understanding of customer needs, internal metrics, and deep knowledge of the broader ML ecosystem to uncover fresh possibilities within our merchant and transaction data sets to bring additional value to our customers and continuously improve on Spade’s product suite
• Identify headcount goals and and collaborate with the recruiting team to identify and hire diverse, excellent engineering talent
• Set clear goals, identify and remove roadblocks, and measure impact of the data organization
• Use project management methodologies to ensure projects are executed on time, within scope, and to Spade’s quality standards
• Nice to have: Own our data pipelines, ensuring that our pipelines are optimized to perform over large data sets, and that we are consistently shipping high quality datasets into production