Location: New York City (remote to start)
We're looking for a seasoned Director of Machine Learning, to help our client accomplish our mission of improving lives by learning from the experience of every cancer patient.
What you will do
In this role, you'll lead teams of data scientists, internally referred to as data insight engineers, who have a strong expertise in discovering, prototyping and launching new data products. The team is an entrepreneurial, customer-focused group that is staffed cross-functionally to drive new data capabilities across the company using machine learning and other advanced analytical techniques. They work to solve complex and exciting problems using data from millions of patients and hundreds of millions of documents to enable novel research on the impact of cancer treatments in the real world, to identify rare patient populations, and to improve the process for matching patients to clinical trials.
As a Director of Machine Learning, you'll have the opportunity to lead these growing teams, partner with senior technical and clinical leaders, and participate in the broader ML-healthcare community through external speaking and publication opportunities.
In addition you'll also:
- Drive the strategic direction and priorities for your teams, leading the exploration to unlock new ML-enabled product opportunities in the real-world evidence (RWE) space
- Directly manage 3-7 data scientists and provide them with hands-on technical guidance and career mentorship while building your leadership bench to support team growth
- Provide data science leadership in a highly ambiguous, impactful, and interesting problem space
- Work cross-functionally across diverse stakeholders, including product managers, software engineers, statisticians, EHR data specialists, and oncologists to set strategy and direction
- Interact with customers, understand their needs to help drive our data products strategy
- Immerse yourself in the business and technical context to help your team identify opportunities to unlock new value from our unique data sets
Who you are
You are an experienced Data Science leader with a background as an entrepreneurial, customer-focused data scientist who enjoys spearheading 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. You are extremely thoughtful about culture and leadership, and you value the diversity of thought and experiences.
- You have 5+ years of experience leading and people managing data teams in an entrepreneurial environment
- You have 10+ years of experience solving technical problems that have a business impact
- You have experience in and are excited to teach others to apply a broad spectrum of techniques from data science and machine learning to solve complex clinical or business problems
- You have led cross-functional initiatives and are passionate about communicating the value of your work to audiences from different scientific and business backgrounds
- You are value-oriented and practical in how you apply data to problems and have empathy for what it means to build sustainable products at scale
- You understand a broad spectrum of methods and disciplines in data science and analytics, and you are especially skilled in at least one of these fields: machine learning, data analytics, decision science, or operations research
- You are comfortable working in production engineering systems
- University training curriculum which includes presentation skills, meeting mastery, coding languages, and more
- Career coaching opportunities
- Hackathons for all employees (not just our engineers!)
- Professional development benefit for attending conferences, industry events, and external courses
- Work/life autonomy via flexible work hours and flexible paid time off
- Generous parental leave (16 weeks for either parent)
- Back-up child care
- fitness classes
Compensation: Up to $390 All-in
To Apply: Send an email to [email protected] or [email protected] or [email protected]