Experienced Data Scientist Needed for Healthcare & AI Consumer Apps

We are looking for an experienced Data Scientist with a strong background in healthcare and AI-powered consumer applications. The ideal candidate will have expertise in analyzing healthcare data, building predictive models, and developing algorithms that enhance user experience. Your role will involve collaborating with cross-functional teams to drive insights and improve our product offerings.

About the Projects

Analyze user scan and submission data to surface insights (e.g., most common harmful ingredients, patterns in ratings)

Support personalization models (e.g., content or product recommendations)

Help clean, structure, and enrich product ingredient data for downstream AI grading

Collaborate with AI/prompt engineers to improve model accuracy and consistency

Work with structured and unstructured clinical data (e.g., brain scans, assessments, EHR/EMR records, physician notes)

Design predictive models for clinical outcomes (e.g., risk scoring, treatment recommendations, triage support)

Collaborate with clinical experts to define relevant features, outcomes, and explainability requirements

Ensure compliance with clinical data handling (HIPAA, PHI standards)

Ideal Candidate Has

3+ years experience as a Data Scientist, preferably in healthcare, digital health, or AI-driven apps

Strong skills in Python, Pandas, NumPy, Scikit-learn, Jupyter

Experience building classification models, working with text + tabular data, and interpretable ML

Familiarity with LLM-powered applications (e.g., OpenAI, embeddings, prompt optimization — nice to have)

Solid understanding of data cleaning, feature engineering, and model evaluation

Bonus: Experience working with OCR (Google Vision) or NLP tasks related to ingredients or health content

Bonus: Familiarity with, psychiatry, or brain health indicators

What Success Looks Like

A robust data pipeline for clean and labeled product/ingredient data

Predictive models supporting clinical workflows with clear explanations for physicians

Actionable user-level insights that make our consumer app smarter over time

Measurable improvements in model precision, rating quality, and personalization

If you have a passion for applying data science in the healthcare sector and possess a strong analytical mindset, we would love to hear from you.

Qualifications

• The ideal candidate will have expertise in analyzing healthcare data, building predictive models, and developing algorithms that enhance user experience
• 3+ years experience as a Data Scientist, preferably in healthcare, digital health, or AI-driven apps
• Strong skills in Python, Pandas, NumPy, Scikit-learn, Jupyter
• Experience building classification models, working with text + tabular data, and interpretable ML
• Familiarity with LLM-powered applications (e.g., OpenAI, embeddings, prompt optimization — nice to have)
• Solid understanding of data cleaning, feature engineering, and model evaluation
• Bonus: Experience working with OCR (Google Vision) or NLP tasks related to ingredients or health content
• Bonus: Familiarity with, psychiatry, or brain health indicators
• A robust data pipeline for clean and labeled product/ingredient data
• If you have a passion for applying data science in the healthcare sector and possess a strong analytical mindset, we would love to hear from you

Benefits

Responsibilities

• Your role will involve collaborating with cross-functional teams to drive insights and improve our product offerings
• Analyze user scan and submission data to surface insights (e.g., most common harmful ingredients, patterns in ratings)
• Support personalization models (e.g., content or product recommendations)
• Help clean, structure, and enrich product ingredient data for downstream AI grading
• Collaborate with AI/prompt engineers to improve model accuracy and consistency
• Work with structured and unstructured clinical data (e.g., brain scans, assessments, EHR/EMR records, physician notes)
• Design predictive models for clinical outcomes (e.g., risk scoring, treatment recommendations, triage support)
• Collaborate with clinical experts to define relevant features, outcomes, and explainability requirements
• Ensure compliance with clinical data handling (HIPAA, PHI standards)
• Predictive models supporting clinical workflows with clear explanations for physicians
• Actionable user-level insights that make our consumer app smarter over time