Senior Data Scientist

Summary

Join Valo Health's Statistical Genetics team as a Senior Staff Data Scientist! Lead teams in applying Valo's Opal computational platform to identify and validate drug targets. Collaborate with data scientists, biologists, software engineers, and clinical development experts. Leverage unique human-centric datasets to solve challenging problems. Lead the application of cutting-edge genetics approaches to discover and develop drug targets using genetic, multi-omic, and clinical data. Lead in matrixed settings composed of diverse scientists, entrepreneurs, and domain experts. This role requires significant experience in statistical genetics and leading teams.

Requirements

• BS + 8-10, MS + 5-8 or PhD + 3-5 years experience in statistical genetics, computational sciences (eg, computational biology, molecular biology), or related fields
• Experience leading matrixed teams, exercising creative problem-solving skills, and demonstrated project management skills
• Experience in performing and working with results of genetically anchored studies
• Demonstrated experience conducting genome-wide association studies (GWAS), and follow up analyses including computing and using (omic)QTL for Mendelian randomization and colocalization
• Demonstrated experience with the computation and application analyses of rare genetic variation (LoF analysis, burden testing, identity-by-descent detection, functional variant annotation)
• Experience working with UKBiobank data or similar datasets, integrating genomics, multi-omics, and clinical information
• Experience with statistical genetics, exploratory data analysis, and data visualization, with a demonstrated business or scientific impact
• Experience developing analysis pipelines and/or software packages
• Proficient in Python or R programming and at least basic knowledge of the other
• Familiarity with working in a command line interface
• Familiarity with writing / developing code using version control (e.g., git) and collaborative code writing practices such as code review

Responsibilities

• Lead project teams of world-class data scientists developing and deploying robust, generalizable solutions to core scientific problems
• Work with a diverse set of stakeholders to develop project plans that support program needs, develop alignment between functional teams and stakeholders, and prioritize
• Work with an array of data types alongside genetic sequencing data, including electronic medical records, 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
• 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

Preferred Qualifications

• 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 disease
• Experience in drug discovery and development

Benefits

$215,000 — $280,000 USD