About Generate:Biomedicines
Generate:Biomedicines is a new kind of therapeutics company – existing at the intersection of machine learning, biological engineering, and medicine – pioneering Generative Biology to create breakthrough medicines where novel therapeutics are computationally generated, instead of being discovered. The Company has built a machine learning-powered biomedicines platform with the potential to generate new drugs across a wide range of biologic modalities. This platform represents a potentially fundamental shift in what is possible in the field of biotherapeutic development.
We pursue this audacious vision because we believe in the unique and revolutionary power of generative biology to radically transform the lives of billions, with an outsized opportunity for patients in need. We are seeking collaborative, relentless problem solvers that share our passion for impact to join us!
Generate:Biomedicines was founded in 2018 by Flagship Pioneering and has received nearly $700 million in funding, providing the resources to rapidly scale the organization. The Company has offices in Somerville and Andover, Massachusetts with over 275 employees.
The Role:
We are seeking a creative and skilled Data Scientist to tackle challenging data problems that are central to our platform capabilities. As a key member of the Data Science team, you will help lead the development of analytical methods and data pipelines to harness our large-scale automated wet-lab capabilities to power our machine learning platform. You will join a talented and collaborative team of ML scientists, engineers, and wet-lab scientists working to redefine how medicines are made. This role is based in our Somerville, MA office with flexibility for hybrid work.
Here's how you will contribute:
- Develop robust analytical pipelines to process, QC, and integrate complex, large-scale experimental datasets to support automated ML applications.
- Design and test innovative end-to-end machine learning pipelines leveraging Generate's wet-lab platform to predict and optimize protein biophysical and functional properties.
- Identify high-value external datasets and integrate them into our machine learning workflows.
- Work with project teams to develop data strategies, and champion best practices around statistical analyses and experimental designs.
- Collaborate with wet-lab scientists and software engineers to build robust analysis pipelines for Generate's high-throughput assay workflows.
- Develop methods and tools to quantify, track, and optimize the quality and consistency of Generate's assay data.
The Ideal Candidate will have:
- PhD in applied quantitative discipline (e.g. Computer Science, Statistics, Computational Biology, Physics, Bioinformatics, etc.) or equivalent industry experience.
- 2+ years experience in an applied team research setting.
- Strong knowledge of probabilistic modeling, statistical inference, and machine learning.
- Demonstrated experience working with high-throughput biological datasets to create robust analysis pipelines.
- A passion for data quality, and an intuition for practical results-oriented solutions.
- Proficiency in Python and experience working in a team setting using software engineering best practices.
- Excellent communication skills and ability to thrive in cross-functional teams.
- Experience in protein science/engineering is a plus.
COVID Safety:
Generate:Biomedicines enforces a mandatory vaccination policy for COVID-19. All employees must be fully vaccinated and have received a booster. The purpose of this policy is to safeguard the health of our employees, their families, and the community at large from infectious disease that may be reduced by vaccinations. The Company will make exceptions to this policy if required by applicable law and will consider requests for an exemption from this policy due to a medical reason, or because of a sincerely held religious belief, or any other exemptions that may be recognized by applicable law.
Equal Employment Opportunity:
Generate:Biomedicines is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
