Data Science Manager, Machine Learning

Added: 9/10/2021

REF: 12903

Contract: Permanent

Location: New York, United States

In this role you will:

  • Lead a team 
  • Work with the managers of cross functional teams
  • Help design solutions in a highly impactful work space with a high degree of autonomy.
  • Understand internal/external feedback to help guide the team’s product roadmap 
  • Lead the technical development effort for data products, analytic tools, and algorithms

The research team is building out the products, software, and algorithms that allow our Scientific customers to advance the state of Oncology 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.

You will also do the following:

  • Manage a team of 2-4 data scientists
  • Work closely with both the product managers and the software engineers  
  • Be accountable for the analytical rigor of the tools/solutions that we come up with
  • Be responsible for taking new product ideas and turning them into production algorithms and products

Must have this experience:

  • Degree in a quantitative field 
  • 6+ years of working experience in an analytical and technical environment
  • Led cross-functional initiatives 
  • Good at influencing decision-making without authority 
  • Prior people management experience  
  • Strong experience evaluating technologies, interviewing customers/end users, and pitching ideas to internal/external stakeholders
  • Okay with working in production engineering systems 

Nice to have this experience:

  • Healthcare experience
  • Experience with open-source software
  • 2+ years of Machine Learning graduate research experience
  • Advanced Degree in a quantitative field

Company Benefits:

  • University training curriculum which includes presentation skills, meeting mastery, coding languages and more
  • Career coaching opportunities
  • Hackathons for all employees 
  • Professional development benefit for attending conferences, industry events and external courses
  • Work/life balance via flexible work hours and flexible paid time off
  • Generous parental leave (16 weeks for either parent)
  • Back-up child care
  • Employee Resource Groups (ERGs) that encourage our employees to share their unique experiences and perspectives
  • Free fitness classes

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