• Strong Python and data science skills; SQL preferred.
• Experience with longitudinal, time-series, behavioral, health, wearable, physiological, or biomarker data.
• Experience using model interpretability and explainability methods: SHAP, LIME, etc.
• Experience in consumer health, digital health, wearables, diagnostics, medical devices, SaMD, or IVD.
• Strong model validation judgment, including handling missing data, avoiding leakage, testing robustness, and evaluating performance across user segments.
• Ability to translate data into user-facing product features, metrics, recommendations, or algorithms.
• Experience building models, scores, or analytical frameworks that influenced product, clinical, or business decisions.
• Strong communication skills with both technical and non-technical stakeholders.
• High ownership, startup speed, and comfort working with ambiguity.
• Good scientific judgment; able to distinguish product insights from clinical or marketing claims.

Nice-to-have:

• Experience with menstrual cycle, fertility, reproductive health, hormones, or women’s health data.
• Advanced degree in a quantitative, biomedical, physics, or health-related field.
• Experience with Bayesian statistics, signal processing, causal inference, survival analysis, or longitudinal modeling.
• Experience moving ML or algorithmic features toward production.
• Familiarity with clinical validation, regulatory documentation, claim substantiation, or peer-reviewed research.

Responsibilities

• Build and improve biometrics, algorithms, and data-driven insights for the Mira App.
• Analyze hormone, cycle, app behavior, and user outcome data to identify patterns and product opportunities.
• Develop and validate models for ovulation prediction, cycle modeling, hormone interpretation, and personalized recommendations.
• Partner with Product, Design, Engineering, R&D, and the Real-World Evidence Scientist to translate data into app features and evidence-backed insights.
• Support RWE and clinical research projects with data extraction, exploratory analysis, modeling, and validation.
• Define model-performance and validation frameworks, including uncertainty, subgroup performance, missing data, and edge cases.
• Improve data quality by identifying instrumentation gaps and recommending better data capture in the app.
• Document model logic, assumptions, limitations, and appropriate use cases clearly for technical and non-technical teams.
• Work with Engineering to move prototypes toward production-ready app features or data pipelines.

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

Location: London, United Kingdom