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About Mira

Mira is a hormone health company headquartered in San Francisco that combines integrative care with hormone testing for more than 300,000 customers. In 2023, the company was named by Inc. 5000 as the fastest-growing femtech business in the United States.

The company’s key innovation is the only FDA-compliant at-home hormone monitor with quantitative testing technology. Its purpose is to make hormone information easy to access and meaningful, helping women make informed decisions about their health through every stage of life, including cycle awareness, family planning, hormone imbalance support, and the menopause transition.

Mira focuses on improving real health outcomes by combining personalized insights, advanced technology, and science-based data into practical guidance for everyday wellbeing.

About the Role

Mira is expanding its hormone health platform with quantitative hormone tracking technology and is looking for a highly capable Data Scientist to become the first member of its data science function. This is a rare opportunity to shape the analytical and algorithmic foundation that will support millions of women in understanding their reproductive health.

In this position, you will define the full research direction, from deciding what should be measured and why to building production-ready algorithms that interpret complex hormone data across varied populations. The work sits at the intersection of reproductive biology, machine learning, and regulated medical device development, and will turn scientific findings into product features used by consumers.

The role reports to the Head of R&D and is expected to evolve into leadership of a data science team as the company grows.

Responsibilities

Create and refine biometrics, algorithms, and data-driven product insights for the Mira app.
Study hormone data, cycle information, app usage, and user outcomes to uncover meaningful patterns and product opportunities.
Design and test models for ovulation prediction, cycle behavior, hormone interpretation, and personalized guidance.
Work closely with Product, Design, Engineering, R&D, and the Real-World Evidence Scientist to convert data into app functionality and evidence-backed insights.
Contribute to real-world evidence and clinical research work through data extraction, exploratory analysis, modeling, and validation.
Establish validation and performance frameworks that account for uncertainty, segment-level performance, missing information, and unusual edge cases.
Strengthen data quality by spotting gaps in instrumentation and recommending better in-app data capture methods.
Clearly record model logic, assumptions, limitations, and appropriate use cases for both technical and non-technical audiences.
Collaborate with Engineering to move prototypes into production-ready app features or data pipelines.

Requirements

Advanced proficiency in Python for data science, with SQL as a preferred plus.
Hands-on experience working with longitudinal, time-series, behavioral, health, wearable, physiological, or biomarker datasets.
Practical use of explainability and interpretability techniques such as SHAP, LIME, or similar methods.
Background in consumer health, digital health, wearables, diagnostics, medical devices, SaMD, or IVD.
Strong judgment in model validation, including managing missing data, preventing leakage, testing robustness, and reviewing performance across different user groups.
Ability to turn data into product features, metrics, recommendations, or algorithms that users can interact with.
Experience creating models, scoring systems, or analytical frameworks that affected product, clinical, or business decisions.
Clear communication skills and the ability to work effectively with both technical and non-technical stakeholders.
Comfort with ambiguity, a high sense of ownership, and the pace of a startup environment.
Sound scientific judgment with the ability to separate product insights from clinical or marketing claims.
Experience with menstrual cycle, fertility, reproductive health, hormones, or women’s health data is preferred.
An advanced degree in a quantitative, biomedical, physics, or health-related discipline is preferred.
Experience with Bayesian statistics, signal processing, causal inference, survival analysis, or longitudinal modeling is a plus.
Prior experience taking ML or algorithmic features into production is a plus.
Familiarity with clinical validation, regulatory documentation, claim substantiation, or peer-reviewed research is a plus.

Benefits

Join a fast-scaling femtech company in the U.S. with a strong mission to improve women’s health and access to care.
Work with a driven, international team committed to making a meaningful difference in people’s lives.
Be part of a fast-moving startup environment where your work has a direct effect on growth, strategy, and major decisions.
Enjoy real growth opportunities, including the chance to help shape and build teams as the company expands.
Work fully remotely with flexibility, autonomy, ownership, and independence.
Receive a competitive compensation package plus a performance bonus linked to OKRs.

Additional Information

This is a full-time remote role for candidates based in the EU. The position is structured as a B2B contract.

Data Scientist