data scientist for women's health

Mira; United States; Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

Performance-based bonus

Job summary

Mira разрабатывает квантитативную технологию отслеживания гормонов для улучшения женского гормонального здоровья и понимания репродуктивного здоровья. Вам предстоит работать над биометрическими данными, алгоритмами и выводами, а также сотрудничать с кросс-функциональными командами для перевода данных в функциональные фичи приложения.

Требуется сильный опыт в Python, работа с временными рядами и навыками валидирования моделей.

Qualifications

• Опыт работы с Python и дата-сайенс.
• Опыт работы с временными рядами, поведенческими и биометрическими данными.
• Опыт применения методов объяснимости моделей (SHAP, LIME).
• Умение валидировать модели и работать с пропусками данных.

Responsibilities

• Анализировать гормональные данные, паттерны и поведенческие данные пользователей.
• Разрабатывать и валидировать модели предсказания овуляции, моделирование цикла и персонализированные рекомендации.
• Сотрудничать с Product, Design, Engineering, R&D и Real-World Evidence Scientist для переноса данных в фичи приложения.
• Участвовать в проектах RWE/клинических исследованиях: извлечение данных, анализ, моделирование и валидация.
• Определять рамки производительности моделей, работу с неопределенностью и подгруппами.

Skills

Python

Data science

Time-series

SHAP

LIME

Model validation

Communication

Startup pace

Tools

SQL

Job description

Описание:

Mira is building quantitative hormone tracking technology to advance women's hormonal health and help people better understand their reproductive health.

Задачи:

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 for technical and non-technical teams Work with Engineering to move prototypes toward production-ready app features or data pipelines

Требования:

Strong Python and data science skills Experience with longitudinal, time-series, behavioral, health, wearable, physiological, or biomarker data Experience using model interpretability and explainability methods such as SHAP and LIME 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 technical and non-technical stakeholders High ownership, startup speed, and comfort working with ambiguity Good scientific judgment and ability to distinguish product insights from clinical or marketing claims Experience moving ML or algorithmic features toward production Будет плюсом: SQL

Условия:

40-Hour workweek with flexible working hours and occasional overlap with the US team Competitive salary and a performance-based bonus system tied to OKRs Career growth opportunities, including the ability to shape, build, and develop teams as the company scales Assessment task as part of the recruiting process The company is a femtech business focused on advancing women's health and expanding access to care