<strong>About Mira<br><br></strong>Mira is a San Francisco-based hormonal health company that provides integrative care and hormonal testing to over 300,000 customers. In 2023, we were recognized by Inc. 5000 as America's fastest-growing femtech company.<br><br>Mira’s breakthrough innovation was creating the market’s only FDA-compliant at-home hormone monitor with quantitative testing technology. From the beginning, our mission has been to make hormone data accessible and meaningful - so women can understand their bodies and make confident health decisions at every stage of life, from cycle health and family planning to hormonal imbalances and the menopause transition.<br><br>We are committed to improving real health outcomes through personalized insights, cutting-edge technology, and science-backed data - turning hormone information into practical guidance for everyday wellbeing.<br><br><strong>About The Position<br><br></strong>Mira is building the future of women's hormonal health through quantitative hormone tracking technology. We're seeking an exceptional <strong>Data Scientist</strong> to be the founding member of our data science function. This is a unique opportunity to define and build the algorithmic foundation that will help millions of women better understand their reproductive health.<br><br>As our first Data Scientist, you will own the entire research agenda - from defining what to measure and why, to building production-ready algorithms that interpret complex hormonal data across diverse populations. You'll work at the intersection of reproductive biology, machine learning, and regulated medical device development, translating cutting-edge science into features that ship in our consumer product.<br><br>This role reports to the Head of R&D and will eventually grow into leading a data science team as we scale.<br><br><strong>Requirements<br><br></strong><strong>Must-have:<br><br></strong><ul><li>Strong Python and data science skills; SQL preferred.</li><li>Experience with longitudinal, time-series, behavioral, health, wearable, physiological, or biomarker data.</li><li>Experience using model interpretability and explainability methods: SHAP, LIME, etc.</li><li>Experience in consumer health, digital health, wearables, diagnostics, medical devices, SaMD, or IVD.</li><li>Strong model validation judgment, including handling missing data, avoiding leakage, testing robustness, and evaluating performance across user segments.</li><li>Ability to translate data into user-facing product features, metrics, recommendations, or algorithms.</li><li>Experience building models, scores, or analytical frameworks that influenced product, clinical, or business decisions.</li><li>Strong communication skills with both technical and non-technical stakeholders.</li><li>High ownership, startup speed, and comfort working with ambiguity.</li><li>Good scientific judgment; able to distinguish product insights from clinical or marketing claims.<br><br></li></ul><strong>Nice-to-have<br><br></strong><ul><li>Experience with menstrual cycle, fertility, reproductive health, hormones, or women’s health data.</li><li>Advanced degree in a quantitative, biomedical, physics, or health-related field.</li><li>Experience with Bayesian statistics, signal processing, causal inference, survival analysis, or longitudinal modeling.</li><li>Experience moving ML or algorithmic features toward production.</li><li>Familiarity with clinical validation, regulatory documentation, claim substantiation, or peer-reviewed research.<br><br></li></ul><strong>Responsibilities<br><br></strong><ul><li>Build and improve biometrics, algorithms, and data-driven insights for the Mira App.</li><li>Analyze hormone, cycle, app behavior, and user outcome data to identify patterns and product opportunities.</li><li>Develop and validate models for ovulation prediction, cycle modeling, hormone interpretation, and personalized recommendations.</li><li>Partner with Product, Design, Engineering, R&D, and the Real-World Evidence Scientist to translate data into app features and evidence-backed insights.</li><li>Support RWE and clinical research projects with data extraction, exploratory analysis, modeling, and validation.</li><li>Define model-performance and validation frameworks, including uncertainty, subgroup performance, missing data, and edge cases.</li><li>Improve data quality by identifying instrumentation gaps and recommending better data capture in the app.</li><li>Document model logic, assumptions, limitations, and appropriate use cases clearly for technical and non-technical teams.</li><li>Work with Engineering to move prototypes toward production-ready app features or data pipelines.<br><br></li></ul><strong>Benefits<br><br></strong><ul><li>Join one of the fastest-growing femtech companies in the U.S., driven by a strong mission to advance women’s health and expand access to care</li><li>Be part of a passionate, highly motivated, and international team dedicated to making a real difference in people’s lives</li><li>Thrive in a fast-paced startup environment where your work directly impacts company growth, strategy, and key decisions</li><li>Enjoy real opportunities for career growth, with the ability to shape, build, and develop teams as we scale</li><li>Work in a flexible, fully remote environment that supports autonomy, ownership, and independence</li><li>Receive a competitive salary along with a performance-based bonus system tied to OKRs</li></ul>