Sr. Quantitative Scientist, Implementation, Infrastructure Lead (Analytic Soluti

As Verana Health reinvents how research happens with data and technology in the healthcare space, we are growing our Data Science team to solve complex real-world problems across multiple therapeutic areas, including urology and ophthalmology. We are looking for a Senior Quantitative Scientist with experience supporting a technical infrastructure that enables scalable, reproducible research and developing code for life science companies to support commercial projects applying real-world data across the clinical development cycle. Direct experience working with ophthalmology or urology clinical data is considered a plus.

You will be embedded within Analytic Solutions, which resides in the Data Science department. This group helps to guide Verana's analytic services offering, which includes insight generation and consultative support on data products directly accessed by commercial partners. Built on the values of learning, collaboration, and rigorous scientific research, the Data Science team strives to improve patient care by innovating at the intersection of real-world, clinical context, and methodology with our partners to ensure all available data is being used to in the most efficient, data-driven way possible.

Job Responsibilities:

Verana Health is looking for a Senior Quantitative Scientist with a background in Engineering, Data Science, Science, Math, Statistics or related skills working specifically in observational data, and collaborating directly with life science companies.

Responsibilities:

• Be a hands-on individual contributor on the Data Science team with a solid grasp of relevant technical approaches (software engineering best practices, healthcare data analytics, programming) and their respective assumptions

• Experience writing readable code for analyses using observational data to create real-world evidence

• Be the technical lead in driving plans fundamental to the team's infrastructure best practices, including GitHub, coding requirements, and analytic workflows

• Influence what important areas to invest in that promote scalable technical processes by framing the business impact

• Work experience on commercial retrospective clinical studies using EHR real-world data through responsibilities such as creation of statistical analysis plans, implementation of analyses, development of algorithms to support research objectives, and/or writing of publications

• Collaborate with teams (e.g., Commercial/Sales, Product, Medical, Engineering/Technology) to translate clinical investigation questions into detailed data analytics requirements for internal and external projects

Basic Requirements:

• Master's or doctorate in a quantitative discipline (e.g., Engineering, Computer Science, Math, Statistics or related field) or equivalent practical experience

• 5+ years of hands-on experience with messy data (e.g., electronic health records, outcomes data) and analytical methodologies

• 5+ years working with life science/pharmaceutical/biotechnology organizations and familiarity with providing analytic services to these groups

• Demonstrated ability to influence a team to adopt best-practices and workflows resulting in higher-quality results and faster turnaround times

• Experience completing research studies for life sciences

• Balance important requirements that produce high-quality, reproducible research while promoting a pragmatic approach

• Advanced skills with data analytics tools, such as SQL, Python, Pyspark, AWS, Git, and Databricks

• Expert in cloud-based architecture and software development and programming principles

• Familiarity with clinical datasets and coding systems such as ICD, CPT, and RxNorm

• Work with cross-functional teams

• Deliver internal/external presentations

  Benefits:

  • We provide 100% health, vision, and dental coverage for employees
  • 401K Match
  • Flexible vacation plans
  • $700 learning and wellness annual stipend
  • $25/wk in Doordash credit
  • Headspace meditation app access