Staff Data Scientist in Epidemiology and Patient Data Products

Valo Health is a human-centric, AI-enabled biotechnology company with the Opal Computational Platform that transforms drug discovery and development through real-world data, AI, human translational models, and predictive chemistry. Our team of biologists, chemists, and engineers works to break down traditional R&D silos and accelerate drug discovery, development, and patient-centric innovation. About The Role

As a Staff Data Scientist in Epidemiology and Patient Data Products, you will be a core member of a team of data scientists advancing the discovery and development of new medicines. You will answer research questions using large real-world healthcare databases to inform identification of biological targets for drug development under the guidance of epidemiology program leads. You will collaborate with colleagues in machine learning, statistical genetics, and computational biology to develop solutions to challenging computational problems, and you will engage with external partners in an innovative startup environment. What Youll Do

Lead real-world data studies (e.g., electronic medical records) from end-to-end to generate causal evidence for projects in drug discovery and development. Translate research questions into observational study designs to generate patient-centric insights from statistical models.

Curation of clinical and non-clinical variables for machine learning models Execution of trajectory modeling techniques using real-world data Interpreting machine learning results into patient profiles Executing post-hoc longitudinal analyses among patient profiles of interest

Be comfortable with scientific uncertainty and embrace curiosity and creative solutions to address problems where solutions are not known in advance. Work with diverse data spanning electronic medical records, sequencing, multi-omics data, and other modalities using R and Python in cloud environments. Break down large problems into solvable pieces and prioritize critical-path work while communicating findings clearly. Collaborate with drug discovery and clinical development teams to ensure the relevance and impact of insights. Be a dynamic and active team member, championing shared coding standards, participating in code reviews, and providing regular updates of your work. You Bring

MS/MPH with 5+ years or PhD in epidemiology or biostatistics with 3+ years of experience applying epidemiology, statistics, and/or machine learning methods to real-world datasets. 3+ years of experience developing and executing robust analytical strategies, including cohort and case-control study designs, using health-care databases such as electronic health records, administrative claims databases, and/or patient registries. Experience leading epidemiologic projects from end-to-end: translating research questions into observational designs, evaluating the strengths and weaknesses of different study designs and statistical approaches, and generating patient-centric insights from models. Extensive experience with causal approaches in observational studies, including propensity score methods, bias adjustment, and covariate selection and adjustment. Advanced knowledge of biostatistics, including inferential and predictive modeling, and experience implementing unsupervised machine learning algorithms in real-world health-care databases. Experience conducting data manipulation and statistical analysis in Python and/or R. Comfort working in ambiguous problem spaces; experience in startup or agile environments as part of cross-functional project teams. Ability to lead and facilitate meetings and collaborate on multi-disciplinary project teams. Exceptional time management and the ability to prioritize multiple tasks and deliver results on time. Enthusiasm for documentation and ensuring analyses are clear and reproducible with thorough documentation of key assumptions and decision points. You May Also Bring

Research experience in obesity, cardiometabolic, and/or neurodegenerative therapeutic areas Experience developing and maintaining machine learning pipelines and translating ML outputs into meaningful insights for diverse audiences Familiarity with or exposure to traditional drug discovery and development processes Hands-on experience curating structured health data and working with health data from outside the U.S. Location: Lexington, MA; offices in New York, NY and Tel Aviv, Israel. Remote options may be available. Employment type: Full-time Seniority level: Mid-Senior level Note: Referrals may increase your chances of interviewing at Valo Health by 2x. #J-18808-Ljbffr