Senior Staff Data Scientist - Statistical Genetics

March 26

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Valo Health

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Valo Health is a company dedicated to revolutionizing the discovery and development of life-changing medicines using high-quality patient data and AI-driven technology. Through its Opal Computational Platform, Valo Health integrates machine learning, tissue biology, and patient data to enhance drug discovery and development processes. The company brings together a diverse team of software engineers, data scientists, biologists, and chemists to harness advanced technology and patient data for innovative healthcare solutions. Valo Health is committed to achieving better health outcomes by accelerating the creation of medicines on behalf of patients worldwide.

51 - 200 employees

🧬 Biotechnology

🤖 Artificial Intelligence

⚕️ Healthcare Insurance

💰 Series C on 2022-10

📋 Description

• 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. • About the Role • As a Senior Staff Data Scientist on the Statistical Genetics team in the Translation Data Science Group, you will lead teams in applying Valo’s Opal computational platform to identify and validate drug targets. • In this role, you will be responsible for leading the application of cutting-edge genetics approaches to discover and develop drug targets using genetic, multi-omic, and clinical data. • What You’ll Do… • 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.

🎯 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.