Machine Learning Engineering Manager, Flatiron Health

• You have an degree in a quantitative field
• You have a minimum of 6 years of working experience in an analytical and technical capacity
• You have led big cross-functional initiatives and are excellent at influencing decision-making without authority
• You have 3+ years of people management experience
• You have extensive experience in evaluating technologies, interviewing customers/end users, and pitching big ideas to both internal and external stakeholders
• You are comfortable working in production engineering systems
• You're an entrepreneurial, customer-focused data scientist who is experienced in driving new data capabilities
• You are excited by the prospect of tackling meaningful problems each and every day
• You are a kind, passionate and collaborative problem-solver who seeks and gives candid feedback, and values the chance to make a real impact on people’s lives

Desirable

• We are looking for a seasoned data science leader to head-up an ML-driven product initiative to help us accomplish our mission to improve lives by learning from the experience of every cancer patient
• In this role, you will empower end users of Flatiron’s data by leading a team focused on enabling our Life Science customers to advance the state of cancer research using real-world data
• As a Staff Machine Learning Engineering Manager, you will work with cross-functional leads to design solutions in a highly ambiguous, impactful, and interesting problem space with a high degree of autonomy
• You will synthesize internal and external user feedback to help guide the team’s product roadmap, lead the technical development effort for data products, analytic tools, and algorithms, and help lead the team to success
• Flatiron’s research team is building out the products, software, and algorithms that allow our Scientific customers to advance the state of cancer research by making use of real-world data
• You will be driving a newly formed team within our Real World Evidence business line
• This team is focused on developing a new set of large-scale, ML-enabled research data products
• Along with working to build these data products, you will be collaborating with a group of data scientists, statisticians, and academics to create the long term scientific vision for how ML can accelerate Real World Evidence research
• This may involve developing and validating novel statistical techniques for using ML-enabled research data in scientific inquiry, as well as developing new classes of ML models
• Manage a team of 4-8 data scientists and machine learning engineers
• Lead the technical trajectory of a team utilizing deep learning and LLM-based NLP models
• Collaborate closely with product managers and the software engineers on the team
• Be accountable for the analytical rigor of the tools/solutions that we come up with
• Be responsible for taking nascent product ideas and maturing them into production algorithms and products