Founding Data Scientist
Summary
Founding Data Scientist at Mira, a women's hormonal health startup: build and validate models (ovulation prediction, cycle modeling, personalized insights) from hormone and app data in Python/SQL, and work with product and engineering to ship them into the Mira App. Fully remote, 40-hour week with occasional US-team overlap.
Mira is building the future of women's hormonal health through quantitative hormone tracking technology.
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.
Requirements:
💦Strong Python and data science skills; SQL preferred and experience with longitudinal, time-series, behavioral, health, wearable, physiological, or biomarker data;
💦Experience using model interpretability and explainability methods: SHAP, LIME, etc;
💦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;
💦Experience moving ML or algorithmic features toward production.
Working conditions:
☘️Remote position;
☘️40-hour workweek;
☘️Flexible working hours;
☘️Occasional overlap with the US team;
☘️Competitive salary with performance-based bonus system tied to OKRs;
☘️Fully remote environment that supports autonomy, ownership, and independence;
☘️Real opportunities for career growth, with the ability to shape, build, and develop teams as we scale.
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