Senior Data Scientist, Statistical Genetics

About Us 

Valo Health is a technology company that is integrating human-centric data and AI-powered technology to accelerate the creation of life-changing drugs for more patients faster. Valo was created with the belief that the drug discovery and development process can and should be faster and less expensive, with a much higher probability of success. We are using models early to fail less often, executing clinical trials to add valuation to the company, and generating fit-for-purpose data to feed back into Valo’s Opal Computational Platform™ as we reinvent drug discovery and development from the ground up. Disease doesn’t wait, so neither can we. 

We are a multi-disciplinary team of experts in science, technology, and pharmaceuticals united in our mission to achieve better drugs for patients faster. Valo is committed to hiring diverse talent, prioritizing growth and development, fostering an inclusive environment, and creating opportunities to bring together a group of different experiences, backgrounds, and voices to work together. We achieve the widest-ranging impact when we leverage our broad backgrounds and perspectives to accelerate a new frontier in health. Valo seeks to become the catalyst for the pharmaceutical industry and drive the digital transformation of the industry. Are you ready to join us? 

About the Role...

As a Senior Data Scientist on the Statistical Genetics team in the Translation Data Science Group, you will contribute to building a computational platform that will change the way we identify and validate drug targets. You will work in a multidisciplinary environment alongside data scientists, biologists, software engineers, and clinical development experts in building a powerful computational platform for advancing the discovery and development of new medicines. Using unique and diverse human-centric datasets, we will solve challenging problems at the interface of scientific discovery, methodology, technology, and software. We are looking for data scientists who can match scientific breadth with technical excellence. 

In this role, you will be responsible for designing experiments and workflows that leverage cutting edge genetics approaches to discover and develop drug treatments using genetic, multi-omic, and clinical data. Successful candidates will work with a diverse set of scientists, entrepreneurs, and domain experts in ways that cut across traditional industry boundaries. 

What You’ll Do… 

• Work as a member of a team of world-class data scientists developing and deploying robust, generalizable solutions to core scientific problems.
• Leverage genetic data to help identify or validate a target for a specific indication and communicate the results to a diverse set of stakeholders.
• Have the opportunity to work with a diverse array of data spanning electronic medical records, genetic sequencing data, multi-omics data, and other data modalities using R or Python in cloud environments.
• Be comfortable with scientific uncertainty and embrace curiosity and creative solutions. Many of the challenges we’re trying to address don’t have known solutions or clear processes to arrive at answers.
• Use your technical knowledge and intuition to articulate and break down large problems into solvable pieces. There are a lot of problems to solve; you’ll need to prioritize which of these are critical today from those that can wait.
• Collaborate with drug discovery and clinical development teams to help ensure the relevance and impact of the insights generated by you and your teammates.
• 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 

What You Bring… 

• BS + 4-8, MS + 3-5 or PhD + 0-3 years experience in statistical genetics, computational sciences (eg, computational biology, molecular biology), or related fields
• Experience performing and working with results of genetically anchored studies:
• Demonstrated experience with the computation and application of polygenic risk scores (PRS) and analysis of rare genetic variation (LoF analysis, burden testing)
• Familiarity with genome-wide association studies (GWAS), computing (omic)QTL, Mendelian randomization, and colocalization, and other functional genomics techniques are a plus
• Expertise in statistical genetics, exploratory data analysis, and data visualization, with a demonstrated business or scientific impact  
• Experience developing analysis pipelines and software packages
• Proficient in Python or R programming and at least basic knowledge of the other
• Experience in writing / developing code using version control (e.g., git) and collaborative code writing practices such as code review 

You May Also Bring…  

• Experience in machine learning, probabilistic graphical modeling, and/or causal inference
• Experience with working with electronic health record data, personally identifiable information (PII), protected health information (PHI) data, or HIPAA compliance
• Experience researching cardiovascular or metabolic diseases
• Experience in drug discovery and development 

More on Valo 

Valo Health, LLC (“Valo”) is a technology company built to transform the drug discovery and development process using human-centric data and artificial intelligence-driven computation. As a digitally native company, Valo aims to fully integrate human-centric data across the entire drug development life cycle into a single unified architecture, thereby accelerating the discovery and development of life-changing drugs while simultaneously reducing costs, time, and failure rates. The company’s Opal Computational Platform™ is an integrated set of capabilities designed to transform data into valuable insights that may accelerate discoveries and enable Valo to advance a robust pipeline of programs across cardiovascular metabolic renal, oncology, and neurodegenerative diseases. Founded by Flagship Pioneering and headquartered in Lexington, MA. Valo also has offices in New York, NY. To learn more, visit www.valohealth.com.