Senior Data Scientist

Based in San Francisco, Nimbus Data Systems is a rapidly growing healthcare technology and clinical services company with a mission to ensure individuals receive the safest and most effective treatments for their unique and evolving healthcare needs. Frequently, medications cause more harm than good. Incorrect drugs and doses costs the US healthcare system over $528 billion in waste, avoidable harm, and hospitalizations each year. Nimbus Data Systems is redefining what excellent healthcare looks like by solving these issues through our software platform (SaaS). We combine cutting edge data science, machine learning, AI, and deep clinical expertise to introduce a patient-centric view to medication management, and develop and deliver personalized care plans on a massive scale for patients and their care teams. Nimbus Data Systems is committed to improving the lives and health of complex patients that have an outsized impact on healthcare costs and have traditionally been difficult to identify and address. These patients face numerous challenges including complicated prescribing issues across multiple medications and providers, medication challenges with many chronic diseases, and patient issues with access to care. Backed by leading healthcare investors and collaborating with top healthcare organizations and providers, we deliver recommendations and facilitate clinical interventions that lead to significant, measurable health improvements for patients and cost savings for customers. Why is Nimbus Data Systems a Great Place to Work?: Outstanding Team and Culture - Our shared mission unites and motivates us to do our best work. We have a relentless passion and commitment to the innovation required to be the market leader in medication intelligence. Making a Proven Difference in Healthcare - We are saving patient lives, and enabling individuals to experience improved health outcomes, including significant reductions in hospitalizations and cost of care. Market Opportunity - Nimbus Data Systems is backed by leading healthcare investors and was founded to tackle one of the largest healthcare problems today. Non-optimized medications therapies which cost the US 275,000 lives and $528 billion annually. Dramatic Growth - Nimbus Data Systems is managing more than 18 million lives across prominent health plans after only 4 years in the market, and was ranked 236 on the 2024 Inc. 5000 list and was named the 5th fastest-growing company in the AI category. This role involves deriving rigorous insights from large, diverse real-world health datasets to support Nimbus Data Systems's mission to improve patient outcomes and lower the cost of healthcare at scale. You'll go beyond prediction to estimate the real effects of medications and interventions on patient outcomes using modern causal inference and causal machine learning methods. This is a dynamic role and an amazing opportunity to help shape the company from the ground up, with many growth opportunities. The Data Science team works with feature-rich, high-volume clinical datasets and collaborates cross-functionally with an experienced team of in-house clinicians, health economics and outcomes researchers (HEOR), engineers, and digital health entrepreneurs. Responsibilities: Design and execute causal analyses of real-world health data to quantify the impact of medications and interventions on patient outcomes and costs Develop, validate, and deploy predictive and causal models and AI tools into Nimbus Data Systems's medication management platform, with careful attention to bias, confounding, and generalizability Partner with clinicians and HEOR researchers to frame questions as well-defined causal estimands and translate findings into clinical and operational decisions Create presentations and reports communicating methods, assumptions, and results to the Data Science team and cross-functional stakeholders Participate in critical reviews within the Data Science team on everything from methods and study design to implementation strategy and code Qualifications: Master's or PhD in Statistics, Biostatistics, Epidemiology, Health Economics, Computer Science, a quantitative/physical science, or a related field Strong foundation in statistical inference and study design, and demonstrated expertise in causal modeling with observational data, e.g., propensity score methods, inverse probability weighting, instrumental variables, difference-in-differences, regression discontinuity, marginal structural models, and target trial emulation Demonstrated, hands-on experience with causal machine learning methods, e.g., double/debiased machine learning, causal forests, targeted maximum likelihood estimation (TMLE), or meta-learners (T-/X-/R-learners)—and familiarity with libraries such as WeightIt, MatchIt, grf, DoWhy, EconML, or CausalML Meaningful experience (3+ years) working with real-world healthcare data (e.g., medical and pharmacy claims or EHR data) and analyzing patient outcomes Experience handling the practical challenges of real-world data: missingness, confounding, selection bias, and measurement error Proficiency with R, Python (scikit-learn, pandas, numpy), and SQL Experience working cross-functionally to define analysis objectives and deliver analytical results Demonstrated ability to work independently, exercise good judgment, prioritize multiple projects, and problem-solve under tight deadlines and resource constraints Excellent written, interpersonal, and presentation skills, including the ability to convey complex technical concepts clearly to audiences with varying levels of technical understanding Bonus: Experience modeling cost-of-care outcomes (e.g., total cost of care, utilization, avoidable spend) in high-risk, high-cost populations Deep experience with advanced difference-in-differences methods and related quasi-experimental designs (e.g., staggered/event-study DiD, synthetic control) Productive use of AI-enhanced coding tools (e.g., Claude Code) in day-to-day development Familiarity with survival analysis and longitudinal/repeated-measures methods Experience deploying models into commercial software products Perks: Joining Nimbus Data Systems offers you a dynamic role and the opportunity to contribute to the company's growth and shape its future. You'll have unparalleled learning and growth prospects, collaborating closely with experienced Clinicians, Engineers, Software Architects, and Digital Health Entrepreneurs. The posted range represents the expected salary for this position and does not include any other potential components of the compensation package, benefits, and perks. Ultimately, the final pay decision will consider factors such as your experience, job level, location, and other relevant job-related criteria. The salary range for this position is: $158000-178000/year. Job Requirements: Ability to pass a background check Must live in and be eligible to work in the United States Information Security Roles and Responsibilities: All staff at Nimbus Data Systems are expected to be part of its Information Security Management Program and undergo periodic training on Information Security Awareness and HIPAA guidelines. Each user is responsible to maintain a secure working environment and follow all policies and procedures. Upon hire, each person is assigned and must complete trainings before access is granted for their specific role within Nimbus Data Systems. Nimbus Data Systems is an equal opportunity employer. We are committed to creating a diverse and inclusive workplace where all employees are treated with fairness and respect. We do not discriminate on the basis of race, ethnicity, color, religion, gender, sexual orientation, age, disability, or any other legally protected status. Our hiring decisions and employment practices are based solely on qualifications, merit, and business needs. We encourage individuals from all backgrounds to apply and join us in our mission. Check our website at https://www.arine.io . This is a unique opportunity to join a growing start-up revolutionizing the healthcare industry! Job Offers: Nimbus Data Systems uses the arine.io domain and email addresses for all official communications. If you received communication from any other domain, please consider it spam. Note to Recruitment Agencies: We appreciate your interest in finding talent for Nimbus Data Systems, but please be advised that we do not accept unsolicited resumes from recruitment agencies. All resumes submitted to Nimbus Data Systems without a prior written agreement in place will be considered property of Nimbus Data Systems, and no fee will be paid in the event of a hire. Thank you for your understanding.