Data Scientist / ML Specialist

About Mira

Mira is a San Francisco-based hormonal health company providing integrative care and hormonal testing for over 92,000 customers. In 2023, they were recognized by Inc. 5000 as America's fastest-growing femtech company. We started our company to help women and individuals reach their parenthood dreams and make their fertility journey smoother.

Mira’s most important breakthrough was inventing the market's only FDA-compliant at-home fertility monitor with quantitative technology. Since the beginning, they have been on a mission to develop data-driven hormonal health solutions to help women make confident health decisions during every stage of their lives—from the menstrual stage to menopause. Mira offers solutions to test, boost, and navigate fertility—starting from comprehensive hormone testing and supplements to fertility coaching and online courses.

We are committed to helping our customers achieve the highest possible success rates and outcomes; that is why our focus is on personalized care, the use of the most cutting-edge technology, and science-backed data.

About The Position

We seek a Data Scientist / ML Specialist for a 3–6 month engagement to upgrade our core product algorithms. This project requires integrating collected data and dynamic modeling techniques to enhance the precision and reliability of predictions. The contractor will collaborate closely with product, medical and engineering teams to deliver practical, production-ready solutions.

If want to challenge yourself at a high-growth startup and make a difference for women's health please join us!

Responsibilities

• Data Collection & Preprocessing
• Labeling & Model Development
• Implement function-based or semi-supervised labeling strategies to create training data for recurring events.
• Build and refine predictive models for recurring events and models for confirmation of the events.
• Feature Engineering
• Design personalized features (historical patterns, user clustering) for better model adaptability.
• Incorporate user demographics and additional data reported by users where appropriate to increase accuracy of the algorithm.
• Iterative Testing & Validation
• Compare new models against baseline metrics and optimize algorithms based on real-world feedback.
• Conduct A/B testing or controlled rollouts for final validation.
• Integration & Documentation
• Collaborate with backend engineers to ensure efficient model deployment and data flow.
• Maintain clear technical documentation for data transformations, model decisions, and performance outcomes.
  
  

Requirements

• Technical Expertise
• Minimum 3 years of experience in data science or machine learning, with a focus on time-series or biological data.
• Modeling & Analysis
• Proven track record in advanced machine learning for adaptive, personalized recommendations or forecasting.
• Familiarity with labeling techniques, semi-supervised learning, or similar methods.
• Data Wrangling Skills
• Capable of cleaning, structuring, and integrating large or messy datasets for model readiness.
• Comfortable with data imputation and handling incomplete user inputs.
• Project Delivery
• Able to manage a defined project scope within 3–6 months, iterating rapidly and adjusting as needed.
• Experience collaborating with cross-functional teams (developers, product managers) on production systems.
• Communication
• Able to communicate results effectively to technical and non-technical stakeholders.
• Willing to provide regular progress updates and clear documentation of all work.

Details

• Short-term remote contract, estimated at 3–6 months.
• Independent role requiring structured progress reports and milestone deliverables.
• Potentially flexible schedule with a requirement for occasional overlap with the product team’s time zone.
  
  

What We Offer

• An opportunity to create a tangible impact in women’s health technology.
• A supportive, collaborative environment that values results and innovation.
• Competitive compensation aligned with expertise and project scope.
• Potential for expanded collaboration following successful engagement.
  
  

Recruiting process

Step 1 ‘Screening call with HR’ - Step 2 ‘Interview Head of Product’ - Step 3 ‘Project review with Head of Product and CTO’ - Step 4 ‘Final interview with the management team (CMO, CTO, CEO, Head of Product)‘