Senior Data Scientist, Clinical Informatics

Location: New York City or Remote USA

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 Clinical Informatics Data Scientist, you will be a core member of a team of data scientists and engineers building a powerful computational platform for advancing the discovery and development of new medicines. In this role, you will develop solutions and execute complex initiatives that leverage real-world data (e.g., electronic medical records, biomedical imaging, time-series data, surveys/questionnaires, and text notes) to address challenging computational problems alongside partner scientists in epidemiology, statistical genetics, computational biology, and machine learning. Successful candidates will work with a diverse set of scientists, and domain experts in ways that cut across traditional industry boundaries in an innovative startup environment. 

What You’ll Do…

• Develop clinical concepts, medical code mappings, and data dictionaries for real-world data types. Maintain data dictionaries used by partner teams and external clients to facilitate high-quality data analysis.
• Define and implement data harmonization standards and curation strategies for real-world patient data products, including data mapping, cleaning and automating ETL pipelines across various data sources.
• Lead the development and maintenance of user-driven tools/packages to generalize data processes and automate data transformation in real-world data studies and machine learning projects. Seek out opportunities to improve these tools/packages from user feedback.
• Collaborate with pre-clinical data science and clinical teams to define data requirements, reconciling research needs with real-world data collection practices and utilization.
• Contribute to writing reports and presentations to non-technical internal audiences and external clients.
• Work in an agile manner to create high-quality, analysis-ready data sets and products to be used across the organization.
• 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.
• 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...

• Bachelor’s with 5+ years or MS / PhD with 1+ years in a medically-related field with a quantitative focus (public health, health economics, biostatistics) or in in a quantitative field (computer science, statistics, computational biology, biomedical engineering).
• Must have 3+ years of experience working with real world data, clinical trial data and/or preclinical data. Practical experience in data cleaning, filtering, and harmonizing real world patient data, and conducting quality and capability evaluations.
• Must have experience developing and maintaining healthcare data dictionaries for patient data.
• Knowledge of medical coding ontologies and data models for real-world data types in US and globally (ICD, ATC, LOINC, SNOMED, CPT, HCPCS, etc).
• Fluency in Python (required) and relevant data science packages (e.g. pandas). Experience in R and SQL a plus.
• Familiarity and/or experience with Spark (pyspark) including performance optimization through query techniques, data storage techniques