Head of Computational Sciences

Posted 16 Days Ago
Be an Early Applicant
South San Francisco, CA
Senior level
Biotech
The Role
As the Head of Computational Sciences, you will lead and manage a team within a biotechnology company, focusing on developing algorithms and machine learning models. Your responsibilities include automating data processes, generating actionable insights from lab data, and collaborating on genomics experiments.
Summary Generated by Built In

Company info

NewLimit is a biotechnology company working to radically extend human healthspan. We’re developing medicines to treat age-related diseases by reprogramming the epigenome, a new therapeutic mechanism to restore regenerative potential in aged and diseased cells. We leverage functional genomics, pooled perturbation screening, and machine learning models to unravel the biology of epigenetic aging and disease using experiments of unprecedented scale.

Description

The Head of Computational Sciences is one of the most senior roles at NewLimit and a member of the Leadership Team. Responsibilities include managing teams, developing algorithms, and writing code across the domains of machine learning, computational biology, and software engineering. You will be responsible for generating actionable insights from data coming out of the lab, which will include automating data orchestration, applying robust statistical methods to parse signal from noise, and training machine learning models to expedite our discovery process. This role owns all computational layers to discover and develop epigenetic reprogramming medicines.

What you'll do

  • Lead, recruit, and manage a team of computational biologists, ML scientists, and software engineers.
  • Plan roadmaps and manage budgets for the Computational Sciences group.
  • Contribute to company-wide decision making.
  • Guide the development of novel algorithms and machine learning models to solve problems at the core of our business.
  • Collaborate with scientists across the company to design and interpret genomics experiments. Automate analyses to expedite our discoveries.
  • Write code. Document APIs. Commit every week. At NewLimit, everyone contributes to the execution of our plans.

Requirements

  • Ph.D. in computational biology, computer science, genomics or a related field with at least 8 years experience
  • Experience building and managing high-performance computational biology teams
  • Experience designing and implementing a production data pipeline in a biotech setting
  • World-class individual contributor (has written a lot of code) in at least one of machine learning, bioinformatics, computational biology, or software engineering

Nice to have

  • Experience contributing to cell and gene therapy products
  • Experience with single cell genomics data, algorithms, and experimental design
  • Familiarity with Bayesian optimization, out-of-distribution prediction models, and biological sequence modeling
  • Experience with AWS, large data pipelines, and dev-ops
  • Startup experience
  • History of building algorithms and software that have been broadly adopted

Benefits

  • Health, dental, and vision insurance
  • 401(k) with company match
  • Industry-leading paid time off (PTO) -- 20 days/year for all employees + holidays
  • Paid parental leave
  • Meals and snacks on-site

Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Learn more at: https://www.newlimit.com/careers   *This compensation and benefits information is based on Company's good faith estimate as of the date of publication and may be modified in the future.

Top Skills

Computational Biology
Machine Learning
Software Engineering
The Company
HQ: South San Francisco, CA
18 Employees
On-site Workplace
Year Founded: 2022

What We Do

NewLimit is a biotechnology company working to radically extend human healthspan. We’re developing medicines to treat age-related diseases by reprogramming the epigenome, a new therapeutic mechanism to restore regenerative potential in aged and diseased cells. We leverage functional genomics, pooled perturbation screening, and machine learning models to unravel the biology of epigenetic aging and disease using experiments of unprecedented scale.

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