Data Scientist, Valo Health
Tissue Engineering
$145-160k
Platform for drug development and discovery
Open for applications
Platform for drug development and discovery
101-200 employees
Open for applications
$145-160k
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
- A Ph.D., Master’s degree +2-3 years’ experience, or BS +3-4 years’ experience, in a relevant computational science field (e.g., computational biology, bioengineering, biostatistics)
- Strong programming skills in Python and proficiency with data analysis libraries database management, as well as versioning of code, data, and models, with additional skills in SQL preferred
- Strong background in data analysis and statistics
- Experience with computer vision and machine learning techniques and tools, such as neural networks, generative models, regression, ensemble learning, regularization, and classification
- Strong familiarity with bioengineering principles and human tissue models preferred
- Familiarity with cardiovascular/metabolic/renal/immune systems in the context of computational biology also preferred
- Excellent problem-solving and critical thinking abilities
- Strong communication skills for effective collaboration and results presentation
- Familiarity with Data and DS best practices; data platforms (data bricks, snowflake); cloud environments (AWS, GCP)
What the job involves
- Join a growing (in vitro modelling) team as a central node connecting our efforts in data science, tissue engineering, and drug discovery
- As a Data Scientist you will use your skills and experience to advance the engineering of human tissue models, focusing on cardiac and skeletal muscle models
- You will be part of a team responsible for developing and building computational models, engineered tissue assays, statistical models, computer vision software, and other machine learning based tools for use throughout our drug discovery pipeline
- Successful candidates will work with a diverse set of scientists, engineers, and domain experts in ways that cut across traditional industry boundaries, building powerful computational tools to advance the discovery and development of new medicines
- Data pipelines, meta-data capture and provenance
- Imaging and time series data processing
- Collaborate with biologists and computational scientists to visualize, preprocess, and analyze large datasets related to human tissue models and bioengineering experiments
- Create clear and informative data visualizations and statistical summaries to communicate findings to technical and non-technical colleagues
- Implement robust validation procedures to ensure reliability and accuracy of tissue engineering and biological model data
- Asist in planning experiments, ensuring data collection is optimized for downstream statistical and analytical purposes
- Develop predictive models and algorithms to identify factors impacting the development, manufacturing and use of tissue models
- Optimize experimental conditions and understand complex biological systems in pursuit of optimal drug candidates
- Model in-vitro phenotypic responses to chemical and genetic perturbations
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
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 values
- Put Patients First
- Succeed As A Team
- There Is No Failure
- Think The Best Of One Another
- Time Is Our Only Limitation
- Take Collective Ownership
Company HQ
Back Bay East, Boston, MA
Articles
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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