Associate Director / Director, Data Science and Engineering

Sorry, this job was removed at 04:20 p.m. (CST) on Tuesday, Feb 17, 2026
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Berkeley, CA, USA
In-Office
185K-253K Annually
Information Technology • Biotech
The Role
Kimia Therapeutics is building a next-generation drug discovery engine that combines a unique
physical platform for high-throughput chemistry and screening with state-of-the-art
computational approaches to accelerate the discovery of novel drugs in cancer and immune
disorders. We are backed by top investors in techbio and therapeutics, including Dimension and
The Column Group, and are led by a veteran leadership team who have built and scaled
multiple new discovery platforms and used them to put multiple drugs into the clinic.

We seek a hands-on leader for the team building the in silico components of ATLAS, spanning
data science, cheminformatics, and software engineering. You and your team impact will both
build the software foundations of ATLAS that tie our high-throughput chemistry and biology
platform into a smoothly humming data engine and drive the data science optimizing its
performance to accelerate drug discovery for Kimia and its partners. This is a startup role in
which you will get your hands dirty with your team in building foundations from the ground up to
transform how chemical optimization and modeling are performed in the industry; the desire to
deliver results and learn rapidly are non-negotiable.

Reporting to the CTO, you will be a hands-on leader for the team building the in silico components of ATLAS, spanning data science, cheminformatics, and software engineering. This is a startup role, and as such it is expected that you will be a hands-on implementor in addition to managing and leading a team. You will serve on the leadership committee for ATLAS, alongside chemistry and biology leads, to drive the execution and build of the platform. Your work will span a broad range of impact, potentially including:

  • Working with the CTO and platform leadership, identify priorities and build the digital execution roadmap aligned with company technical and discovery strategy.
  • Collaborate with laboratory scientists to define specific requirements for each components this roadmap
  • Drive execution on this roadmap spanning science and engineering, both through your team and through your own effort as needed.
  • Build and manage a multidisciplinary team, setting a culture of delivery, rapid systematic iteration, and high growth.
  • Present externally and internally in both scientific and business contexts as needed, potentially including conferences, partnering, and fundraising discussions.

Experience and Skills

  • BS in computer science, mathematics, chemistry or a related field. Demonstrated excellence in prior work is more critical than exact undergraduate coursework.
  • 5+ years work experience as a senior technical contributor in two or more of software engineering, data science, and/or machine learning products; experience applying these in the context of chemistry, biology, and/or drug discovery is preferred.
  • Experience building software to drive laboratory operations is preferred.
  • 1.5+ years of personnel management and team leadership experience, including recruiting, day-to-day management, mentoring, performance evaluation, and team strategy development.
  • A track record of technical leadership excellence in these fields, as evidenced by presentations, publications, or output from teams formerly led.
  • Excellent oral and written communication skills

We offer a vibrant startup environment where every member of the Kimia team plays an
important role in shaping our science and our culture. Kimia offers competitive pay, participation
in our stock option plan, and comprehensive benefits. At Kimia we believe that a diverse, open
and inclusive environment is key to our success. We are proud to be an equal opportunity
employer and will consider all applicants for employment.

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The Company
Berkeley, , California
33 Employees
Year Founded: 2023

What We Do

Unlocking deeper insights from empirical data in the pursuit of better medicines

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