Data Scientist (Medical Predictive & Longevity)
Role Description
We’re seeking a highly skilled and motivated Data Scientist to take an early, high-ownership role delivering SOTA models in the core of our health tech startup.
Our mission is to democratize longevity by providing personalized, AI-driven health insights. Your goal is to translate complex human biological data into actionable health scores and personalized recommendations. You will focus on building predictive models that assess the probability of systemic health events and developing recommendation engines that match users with the most effective advices. Accuracy, statistical significance, and interpretability are your main KPIs.
Key Role Outcomes
- Predictive Health Models: Develop and validate ML models that predict the probability of specific health scores based on biomarkers and user history.
- Personalized Recommendation Engine: Build a scoring system that prioritizes health check-ups and supplements tailored to the user's unique "longevity profile."
- Data preparation: Prepare and refine datasets for developing predictive models. Initiate data-collection process from various sources.
- Data Reliability: Ensure the medical datasets are clean, normalized, and properly imputed, handling the noise inherent in real-world health data.
- Scientific Validation: Conduct statistical analysis to prove that our algorithms provide significantly better recommendations than generic advice.
Responsibilities
- Gather, clean, and preprocess health data from different sources and user data to ensure accuracy and relevance in health assessments.
- Design, create, and implement machine learning models, to generate personalized health advice and scoring tailored to individual user profiles.
- Collaborate with Product, Science experts to to translate medical insights into effective data-driven applications.
- Perform model validation to ensure medical accuracy and avoid overfitting.
- Analyze "Feature Importance" to explain to doctors and users why a specific recommendation was made (Explainable AI).
Requirements
Must Have:
- Bachelor’s degree in a quantitative discipline (Mathematics, Statistics, Computer Science, Engineering, Bio-informatics); Master’s or PhD is a significant plus.
- 5+ years proven experience in Data Science or a similar role, with a focus on machine learning and predictive modeling.
- Proficiency in Python and experience with data manipulation libraries (Pandas, NumPy) and machine learning frameworks (TensorFlow, PyTorch).
- Strong SQL skills for querying and managing large datasets.
- Solid understanding of statistics with the ability to evaluate model performance effectively.
- Ability to communicate complex data findings to non-technical stakeholders clearly.
- Experience with data visualization tools to present insights.
- Strong problem-solving skills with a proactive approach to data challenges.
Good to Have:
- Experience in the health tech industry or knowledge of healthcare data regulations.
- Familiarity with cloud platforms (AWS, Google Cloud, Azure) for deploying models and managing data pipelines.
- Understanding of DevOps practices, including version control (Git) and CI/CD.
- Experience with causal inference (understanding correlation vs. causation in health).
Want to apply?
Please send you CV to anna@sfdstrategy.com or Telegram: @AnnaAlign
