Reify Health is changing the way medicines are developed by connecting and empowering the clinical trial ecosystem. We are a team of researchers, entrepreneurs, technologists, and healthcare-obsessed professionals building solutions that eliminate some of the biggest challenges in clinical research.
We care about the people who care for people...and we have fun while doing it.
Our unique, rapidly growing data streams are enabling unique opportunities to manage clinical trials more efficiently and predictably. The Data Analytics & Data Science group is looking for talented Senior Data Scientists to explore our data and distill novel insights which will unlock these opportunities for clinical professionals. If you're empathetic, results-driven, and want to put your unique analytical skills to work to help the clinical research community then this may be the role for you.
As a fast-growing startup, we're looking for people who can effectively balance rapid execution and delivery with statistical/mathematical rigor to serve the business most effectively. You have strong opinions, weakly held, and while well-versed technically know when to choose the right tool, for the right job, at the right level of complexity. You will work in alignment with our Data Engineering and Data Products groups, benefitting from their architecture, tooling, and technical expertise, and also collaborate on projects with company stakeholders across Design, Product, and Software Engineering.
What You'll Be Working On
- Exploring rich historical data from clinical sites, pharmaceutical sponsors, and other stakeholders and use it to uncover applicable insights to help our sites and sponsors make more effective trial support and enrollment management decisions as early as possible.
- Work with our Data Products group to productionize your insights and models into recommendation systems and other intelligent features for our users.
- Perform statistical analyses and support the analyses of our analytics team to demonstrate the relative efficacy of StudyTeam to key stakeholders.
- Developing deep familiarity with HIPAA, GDPR, and other applicable regulatory and privacy frameworks and how they influence our analysis and model development decisions.
- Regularly communicating your insights with a wide variety of technical and non-technical stakeholders in clear written, verbal, or presentation form.
- Living our data philosophy, which focuses on ethical decision making, being aware of how biased data (and assumptions) can affect results (and people), and being laser-focused on business needs.
What You Bring to Reify Health
- At least 5 years of professional work experience in an applied data science role dealing with regulated health or clinical data (or similar highly regulated dataset).
- Expertise in several techniques including NLP, supervised/unsupervised learning, Bayesian/frequentist (bio)statistics, linear optimization, neural networks, and linear/nonlinear regression.
- Experience with developing or integrating clinical or other medical taxonomies and ontologies.
- Deeply understands not only how to use a technique but why it is or is not appropriate in a given situation, with available data, and for specific business needs.
- Familiarity (or ability to become familiar) with privacy-preserving or identity protecting techniques such as differential privacy, privacy-preserving GAN, etc.
- Expertise in at least one of the following: Clojure, Python, or R (and deep familiarity with corresponding analytics and data processing libraries).
- Familiarity with various database, warehouse, and streaming platforms such as PostgreSQL, Redshift, and Kafka.
- Familiarity with AWS ecosystem (Athena, Glue, Redshift, S3, Lambda).
- Understanding of the nuances of testing and addressing scalability/accuracy of analytical processes in distributed/probabilistic systems.
- Advanced degree in computer science, biostatistics, or other related field.
- Relevant published or publicized professional or academic work such as open-source contributions, blog posts, or publications.
- Develop or expand enrollment prediction models for existing trials.
- Collaborate on solutions to optimize enrollment planning for new trials.
- Optimize the logistics, resourcing, and orchestration of complex trials.
We value diversity and believe the unique contributions each of us brings drives our success. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Note: We are unable to sponsor work visas at this time.