FemTech / Fertility Algorithm & Data Science Consultant

We are developing a fertility and cycle-tracking platform, and are seeking an experienced FemTech Data Scientist, Reproductive Health Algorithm Specialist, or Health Data Scientist to design the backend logic powering our menstrual cycle and fertility predictions. This is NOT a general mobile app development position. We already have developers. We need a specialist who can design the scientific logic, algorithms, calculations, decision trees, and data models that our developers will implement. What We Need Built The consultant will help design a comprehensive cycle and fertility prediction engine including: * Personalized menstrual cycle length calculations * Next-period prediction * Cycle variability and irregular-cycle detection * Fertile-window prediction * Personalized ovulation estimation * Luteal-phase estimation * LH/OPK surge and peak detection logic * Integration of quantitative LH test results * BBT trend analysis and ovulation confirmation logic * Cervical mucus fertility indicators * Dynamic predictions that update as new cycle data is entered * Prediction confidence scoring * Handling incomplete or missed cycle data * Abnormally long/short cycle handling * Possible anovulatory-cycle logic * Pregnancy-mode transition * Postpartum/breastfeeding considerations * Recently discontinued hormonal contraception considerations * Appropriate handling of insufficient data/new users The system should distinguish clearly between: * Predicted period dates vs. logged period dates * Predicted ovulation vs. biomarker-supported ovulation * Calendar estimates vs. current-cycle physiological evidence * Low-confidence vs. high-confidence predictions Test Strip Integration Lunara will also integrate with physical LH and HCG test strips. We are especially interested in candidates with experience in: * OPK/LH test interpretation * T/C ratio calculations * Computer vision for test strips * LH baseline and surge detection * Peak detection * Image-processing pipelines * Fertility biomarker interpretation Computer-vision expertise is preferred but not required for the initial algorithm specification. Data Inputs The future prediction engine may use: * Period history * Cycle length history * LH tests * Basal body temperature * Cervical mucus * Symptoms * User-entered ovulation information * Pregnancy tests * Wearable/device data * Sleep and other physiological data We want an architecture capable of incorporating additional biomarkers in the future. Deliverables The primary deliverable should be an implementation-ready Cycle & Fertility Algorithm Specification for our development team. This should include: 1. Mathematical calculations/formulas 2. Variables and required data inputs 3. Database/data-model recommendations 4. Decision trees 5. Pseudocode 6. Prediction-confidence methodology 7. Cycle-learning/personalization methodology 8. Irregular-cycle logic 9. LH interpretation logic 10. BBT interpretation logic 11. Fertile-window calculations 12. Missing-data handling 13. Edge cases 14. New-user/default logic 15. Testing scenarios and expected outputs 16. Recommendations for validating prediction accuracy 17. Clear documentation our backend developers can implement We are **not looking for someone to simply use a standard 28-day cycle calculation.** The goal is to develop a personalized system that learns from each user's historical and current-cycle data and appropriately changes its predictions as new information becomes available. Ideal Candidate We would especially like to hear from candidates with experience in one or more of the following: * FemTech * Fertility technology * Menstrual-cycle modeling * Reproductive-health research * Digital health * Biostatistics * Time-series modeling * Health data science * Machine learning * Physiological signal processing * Fertility-awareness methods * Consumer health applications Experience working with fertility or menstrual-cycle datasets is **strongly preferred**. Python/R experience is preferred. Clinical or academic reproductive-health experience is a major plus. Important Lunara combines scientific cycle tracking with separate wellness and spiritual features. The **scientific fertility prediction engine must remain evidence-based and independent** of spiritual features such as moon phases, journaling, mindfulness, and intention setting. We want someone who understands the importance of scientific integrity, user safety, privacy, explainability, and not presenting uncertain predictions as medical certainty. When Applying Please include: * Your relevant experience with menstrual-cycle, fertility, reproductive-health, or physiological data * Examples of health algorithms/models you have developed * Your experience with time-series or longitudinal health data * Whether you've worked with LH, BBT, hormone, wearable, or fertility data * Whether you can provide implementation-ready pseudocode/documentation * How you would approach validating the algorithm * Your estimated timeline and project cost **Please do not apply if your experience is limited to general mobile/web development. We are specifically seeking someone who can design the fertility/cycle intelligence layer.**