Senior Data Scientist - Healthcare Analytics

Application Eligibility Criteria

Please apply to this position only if you meet all of the following mandatory requirements:

1. A minimum of 6+ years of experience in the Healthcare industry.
2. Hands-on experience in causal inference and experimentation.
3. Willingness to join as a full-time employee (no C2C or W2 arrangements).
4. You have not applied within the past three months to a similar role.
   

About the Role

📍 Hybrid (NY / NJ)

💼 Full-Time

✈️ Visa Sponsorship Available

Role Overview

We are seeking a Senior Data Scientist to support advanced analytics initiatives across a healthcare portfolio, with a strong focus on patient outcomes, real-world evidence (RWE), and data-driven decision-making. This role involves working extensively with complex healthcare datasets—including claims, EHR, laboratory data, and social determinants of health (SDOH)—to generate insights and evaluate the impact of clinical and operational interventions.

This is a hands-on leadership role, combining individual technical contribution with the responsibility of leading cross-functional teams to deliver measurable business and clinical outcomes.

Key Responsibilities

• Analyze large-scale healthcare data, including medical and pharmacy claims, EHR, laboratory data, and SDOH
• Design and execute real-world evidence (RWE) studies
• Apply statistical, causal, and quasi-experimental methods to assess intervention impact
• Develop predictive and analytical models to support population health initiatives
• Analyze patient journeys, care patterns, and provider networks
• Identify healthcare disparities and access barriers
• Translate complex analyses into clear, actionable insights for business and clinical stakeholders
• Build and maintain dashboards and reporting solutions
  

Required Skills & Experience

• 3+ years of experience working with healthcare data such as medical and pharmacy claims, EHR, labs, or SDOH
• 6+ years of hands-on experience applying statistical techniques, including hypothesis testing, regression modeling, and causal analysis
• Strong experience conducting cohort analysis and quasi-experimental evaluations
• High proficiency in SQL for large-scale data analysis
• Strong working knowledge of Python or R for statistical modeling and analytics
• Proven ability to translate complex analytical findings into business-relevant insights
• Solid understanding of metrics, experimentation frameworks, and performance measurement
  

Nice-to-Have Qualifications

• 3+ years of experience with A/B testing
• 6+ years of experience using SQL
• 3+ years of hands-on experience in hypothesis testing