Senior Data Scientist - Real World Data

Scorpion Therapeutics; Chapel Hill (NC); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Scorpion Therapeutics is seeking a Senior Data Scientist to join the Scientific Data Intelligence team in transforming Real World Data from EHR and claims into actionable scientific insight for drug development.

You will build scalable data pipelines, model healthcare data to OMOP standards, and conduct observational studies to illuminate disease epidemiology and treatment patterns. Hybrid setup with relocation options in major US hubs.

Qualifications

• 5+ years in data science or data engineering with healthcare or life sciences experience.
• Proficient in SQL, Python, and modern data tools.
• Knowledge of biomedical schemas (UMLS, LOINC, ICD) and RWD study design.
• Experience constructing longitudinal cohorts and observational studies.
• Familiar with regulated data environments and commercial RWD vendors.

Responsibilities

• Develop scalable data pipelines using SQL, Python, Dagster, dbt, and Snowflake.
• Model and clean healthcare data adhering to OMOP standards.
• Conduct observational RWD studies on epidemiology, treatment patterns and patient journeys.
• Implement data validation and observability.
• Apply Generative AI to enhance data structuring and insights.
• Communicate findings to technical and non-technical stakeholders.

Skills

RWD data science

Observational studies

Causal inference

Data validation

Generative AI

Stakeholder communication

Tools

SQL

Python

Dagster

dbt

Snowflake

OMOP

UMLS

LOINC

ICD

Job description

Role: Senior Data Scientist within the Scientific Data Intelligence team, focusing on transforming and analyzing Real World Data (RWD) such as EHR and claims to support drug development and scientific decision-making.

• develop scalable data pipelines using SQL, Python, Dagster, dbt, and Snowflake;
• model and clean healthcare data adhering to standards like OMOP;
• conduct observational RWD studies on disease epidemiology, treatment patterns, and patient journeys;
• implement data validation and observability;
• apply Generative AI techniques to enhance data structuring and insights;
• communicate findings to technical and non-technical stakeholders.

Requirements:

• 5+ years in data science or data engineering, with at least 2 years' experience in healthcare or life sciences, including hands-on work with EHR or claims data;
• proficiency in SQL, Python, and modern data tools;
• knowledge of biomedical schemas (UMLS, LOINC, ICD), RWD study design, and causal inference frameworks;
• experience constructing longitudinal cohorts and executing observational studies;
• familiarity with regulated data environments and commercial RWD vendors preferred.

HighValue: healthcare data science, RWD transformation, Generative AI, disease epidemiology, causal inference, longitudinal cohort construction, regulated data handling.

WorkSetup: hybrid model in NYC, Boston, Research Triangle, or Bay Area, requiring 3 days onsite; some relocation or residence in these locations necessary.