Senior Staff Data Scientist, Valo Health
Translational Data Science
$236.1-264.2k
Platform for drug development and discovery
Job no longer available
Platform for drug development and discovery
101-200 employees
Job no longer available
$236.1-264.2k
101-200 employees
Company mission
To make the drug discovery and development process faster, less expensive, and with a higher probability of success.
Role
Who you are
- MS or PhD in a quantitative field with a demonstrated experience at the intersection of deep learning and knowledge graphs
- Advanced knowledge of and extensive experience with graph ML techniques such as Graph Neural Network (GNN) models applied to link prediction, node classification, and other biomedical-relevant computational tasks, as well as related explainability methods
- Experience or general knowledge of knowledge-graph building and graph databases
- Familiarity with general graph algorithms and relevant Python libraries
- Strong experience in Python and at least one deep-learning framework (e.g., pytorch)
- Experience with data science best practices (data provenance, code versioning, reproducibility, etc), large-scale data analytics engines (e.g., Spark or Dask), and working in cloud environments (e.g., AWS)
- Experience in healthcare, medicine, molecular biology, computational biology, or life sciences preferred
- Familiarity with or exposure to traditional drug discovery and development processes and approaches is a plus
What the job involves
- As a Senior Staff Scientist ML within the Translational Biology Data Science department, you will be a core member of a team of data scientists, software engineers, and translational biologists building a powerful computational platform for advancing the research and development of new medicines
- You will develop graph ML solutions to make available a vast corpus of knowledge in medicine, molecular biology, human genetics, and drugs available to machine learning-based strategies and compute-enabled hypothesis generation
- Successful candidates will work with a diverse set of scientists, entrepreneurs, and domain experts in ways that cut across traditional industry boundaries
- Work as part of teams of world-class data scientists and engineers developing and deploying robust, generalizable solutions to core scientific problems
- Be comfortable with scientific risk - many of the challenges we’re trying to address don’t have known solutions
- Use your technical knowledge and intuition to articulate and break down large problems into solvable pieces. Time is limited, you’ll need to prioritize which problems are critical-path today from those that can wait
- Collaborate with drug discovery and clinical teams to help ensure the relevance and impact of the models, algorithms, or knowledge representation developed by you and your team
- Be a dynamic and active team member, championing and adopting shared coding standards, participating in code review, and providing regular updates of your work and input into the work of your colleagues
Our take
Drug development is a critical component of health care. Reducing costs, improving discovery processes, and accelerating drug development are all critical to success in the drug pipeline. Using human-centric data and ML-anchored computation, Valo Health’s integrated drug development platform, known as Opal, improves outcomes in drug development, by leveraging advanced data analysis.
Drug development entails a variety of steps including molecule discovery, clinical development, and target discovery. With the vast amount of data that is generated, a system like Opal incentivizes investment in outcomes that are more likely to correspond with effective treatments. This reduces the number and expense of clinical trials needed to demonstrate drug effectiveness.
There are a variety of competitors in the data-driven drug discovery field, including insitro, Atomwise, and Exscietia, but this vast market should still offer enough space for Valo Health to grow. In 2021, the company experienced a set-back in the surprise calling off of a merger that would have seen it go public, but despite this has continued to operate well and advance towards its goal of transforming the drug development process.
Freddie
Company Specialist at Welcome to the Jungle
Insights
-23% employee growth in 12 months
Company
Funding (last 2 of 7 rounds)
Nov 2021
$1m
LATE VC
Jul 2021
$33.5m
LATE VC
Total funding: $487.5m
Company benefits
- Medical, Dental, and Vision Insurance
- Flexible Time-off
- 401K
- Corporate Engagement Opportunities with Local Non-Profit Organizations
- Commuter Reimbursement
- Fitness Reimbursement
- Pet Insurance
Company HQ
Back Bay East, Boston, MA
Leadership
Brian Alexander
(CEO)Also a Partner at Flagship Pioneering. Previously SVP of Genentech, CEO of Foundation Medicine and was a n Associate Professor at Harvard Medical School.
Brett Blackman
(COO)Member of the Board of Directors at Stanley Manne Children's Research Institute. Previously Interim Chief Scientific Officer at Omega Therapeutics and was a Strategic R&D Advisor at Ohana Biosciences, Inc.
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