Senior Quantitative Science Manager, Machine Learning at Flatiron Health
We are looking for a senior quantitative scientist leader with expertise and experience in a healthcare-related quantitative research field to help us accomplish our mission to improve lives by learning from the experience of every cancer patient. Here is what you need to know about the role, our team and why Flatiron Health could be the right next step in your career.
What You’ll Do
The Machine Learning (ML) initiative develops our machine learning capabilities to support internal and external clients in identifying cohorts of patients with certain characteristics, in developing ML-extracted or -derived variables to complement data from Electronic Medical Records (EMR), and in developing some of our data registries and analytical products. We are looking for a senior quantitative scientist leader with experience working in a cross-disciplinary environment, in training and collaborating with more junior members of the team and, preferably, in leading complex client-facing engagements. Furthermore, as a manager, you will work with other Quantitative Sciences (QS) team members to answer some of the most important questions in cancer research and drug development using Flatiron’s unique, rich, large real-world data (RWD). As a leader on this team, you will:
- Contribute to the strategic and analytical roadmap of the ML team
- Leverage statistical, epidemiological and outcomes research subject matter expertise, as well as a solid understanding of our data models and RWD-appropriate analytic methods, to provide recommendations on appropriateness of different analytical strategies (including sign-off), and to inform the work in ML to ensure the team is building relevant and impactful solutions
- Propose and advocate for novel ML use cases across the organization
- Manage QS members in the ML team
- Coach and provide career and technical mentorship to direct reports
- Collaborate with the QS ML team members and QS leadership team to further develop a vision for what it means to be doing ML as a QS member
- Enable and unblock QS members to be accountable for assessing project feasibility, developing and executing SAPs, and presenting and iterating results to cross-disciplinary audiences
- Evaluate QS resourcing needs for current and future projects in collaboration with cross-disciplinary leadership
- Ensure adherence to business processes, encourage consistent approaches across QS and the broader business with respect to analyses, ensure data quality standards and enforce best practices
- Collaborate with internal and external stakeholders
- Collaborate with other QS managers for functional initiatives
- Collaborate with cross-disciplinary stakeholders (e.g., software engineers, data insights engineers, product managers, clinical data specialists, research oncologists) on a joint mission of thoughtfully increasing the impact of ML at Flatiron
- Lead Flatiron in technical/statistical/analytical discussions with clients
- Provide internal and external outreach through presentations at Flatiron’s internal scientific forums and at scientific conferences
- Publish scientific work in peer-reviewed journals
Who You Are
You are an analytical thinker with relevant work experience in an academic or industry setting. You are excited by the prospect of rolling up your sleeves to tackle 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 an important impact.
- You hold a PhD in a quantitative discipline such as biostatistics, epidemiology, applied statistics, health economics, or a related discipline, with at least two years of relevant industry experience
- Alternatively, you hold a Masters in one of the quantitative disciplines aforementioned and at least six years of relevant industry experience
- You have experience collaborating with researchers in the life science industry, academia, or government agencies
- You have some leadership experience with predictive modeling or machine learning
- You enjoy being a people’s manager, and are a natural teacher; you have a passion for mentoring and coaching those of various backgrounds and levels of experience
- You have the ability to juggle multiple internal and external interactions and deadlines simultaneously, and the adaptability to collaborate with individuals at all levels and disciplines
- You have excellent written and oral communication skills and a deep attention to detail
- You are comfortable with doing some level of project work (approximately 30%); requiring some R or Python coding
- You are independent, self-motivated, self-directed and proactive
- You can represent the data and analysis strategy, and get in the technical weeds to explain it to our customers
If this sounds like you, you'll fit right in at Flatiron.
- You have oncology experience
- You have healthcare consulting experience
- You have experience working with longitudinal EMR data
Why You Should Join Our Team
A career at Flatiron is a chance to work with many bright people involved in the future of cancer care and research: researchers, data scientists, clinicians, technologists and many more, all working together to improve cancer care and accelerate research.
You'll also find a culture of continuous learning, broad and inclusive employee support offerings, and a commitment to supporting our team members in all aspects of their lives—at home, at work and everywhere in between. We offer:
- Flatiron University training curriculum which includes presentation skills, meeting mastery, coding languages and many 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
- Flatiron-sponsored fitness classes
Flatiron Health is proud to be an Equal Employment Opportunity employer.
We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.