Data Scientist - women's hormonal health (Remote, B2B contract)

About Mira 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. 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. 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. About The Position Mira is building the future of women's hormonal health through quantitative hormone tracking technology. We're seeking an exceptional Data Scientist 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. 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. This role reports to the Head of R&D and will eventually grow into leading a data science team as we scale. Requirements Must-Have: • PhD strongly preferred in Reproductive Biology, Endocrinology, Biostatistics, Computational Biology, or related field • Deep domain expertise in reproductive endocrinology or women's hormonal health - you understand the physiology, not just the data patterns • Hands-on experience with hormonal/menstrual cycle data or clinical biomarker data • Production coding: Proficient in Python (pandas, scikit-learn, NumPy)—able to write code that ships, not just notebooks • Publication record demonstrating rigorous scientific thinking • Strong opinions about what's wrong with current cycle tracking methods and why Technical Skills: • Time series analysis, signal processing, Bayesian statistics • Machine learning and model validation • Experience with messy, real-world physiological data • Understanding of clinical study design and regulated medical devices (IVD/510k) is a plus Details The role is a remote position, with a 40-hour workweek, flexible working hours, and occasional overlap with the US team. Responsibilities • Design and validate algorithms for hormone interpretation, ovulation prediction, and cycle modeling across diverse populations • Conduct rigorous validation studies and publish peer-reviewed research to establish scientific credibility • Build production-ready code that ships in the Mira App (Python, data pipelines, ML models) • Collaborate with Product, Hardware, Clinical, and Regulatory teams to translate research into features • Support clinical validation and regulatory submissions • Eventually build and lead the data science team Benefits • 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 • Be part of a passionate, highly motivated, and international team dedicated to making a real difference in people’s lives • Thrive in a fast-paced startup environment where your work directly impacts company growth, strategy, and key decisions • Enjoy real opportunities for career growth, with the ability to shape, build, and develop teams as we scale • Work in a flexible, fully remote environment that supports autonomy, ownership, and independence • Receive a competitive salary along with a performance-based bonus system tied to OKRs

Want to see how well you match this job?