Partner Data Analyst - Life Science Partnerships

About the role

Truveta is seeking a highly skilled Partner Data Analyst to join our dynamic life science partnerships team. In this role, you will serve as a critical technical resource for our clients, helping them leverage our extensive real-world Electronic Health Record data to advance their research initiatives. Your primary responsibilities will include translating complex research questions into actionable analytical strategies, providing technical support during customer interactions, and ensuring the delivery of high-quality analyses that meet client needs. The ideal candidate will possess a strong background in data science, epidemiology, or biostatistics, combined with excellent communication skills and a passion for supporting innovative healthcare research. This position offers an exciting opportunity to work at the intersection of data, healthcare, and research, contributing to projects that have the potential to impact patient outcomes and scientific understanding.

Key facts

What you'll do

• Collaborate closely with life sciences clients to understand their research questions and objectives, translating these into clear, actionable analytical plans.
• Provide expert technical support during customer calls, assisting clients with troubleshooting issues related to their analyses, code, or data queries.
• Utilize SQL, R, and Python to scope, develop, and execute customer analysis requests, ensuring timely and accurate delivery of results.
• Build and nurture strong relationships with customer stakeholders, including researchers, data scientists, and project managers, to facilitate ongoing collaboration and trust.
• Apply relevant research methodologies, such as cohort design, statistical analysis, and bias mitigation techniques, to ensure methodological rigor and validity of results.
• Communicate project progress, findings, and insights effectively to both technical and non-technical audiences, including success managers and executive stakeholders.
• Offer guidance on best practices for real-world data research, including study design considerations, confounding factors, and interpretation of results.
• Lead discussions with clients to address research challenges, clarify requirements, and keep projects on schedule.
• Support customers in preparing and publishing peer-reviewed research articles, white papers, and other high-quality outputs that demonstrate the value of Truveta's data platform.
• Perform quick-turnaround analyses to answer urgent client questions, as well as more comprehensive, in-depth investigations for long-term projects.
• Provide ongoing technical troubleshooting support for customer notebooks, code, and analysis pipelines to ensure smooth operation and accurate results.
• Develop and update training materials, tutorials, and documentation to onboard new researchers and users as the platform evolves.
• Collaborate with internal teams to assess data quality, identify data gaps, and demonstrate the reliability and robustness of the data assets.
• Gather and relay customer feedback to product and engineering teams to inform platform improvements, new features, and data enhancements.
• Participate in cross-functional meetings to align on project goals, share insights, and contribute to the continuous improvement of the platform and services.

Requirements

• Bachelor's or master's degree in clinical research, epidemiology, biostatistics, data science, clinical informatics, or a related field.
• Minimum of 5 years of experience in a technical customer-facing role, delivering research studies, analyses, or similar projects.
• At least 3 years of experience managing and analyzing Electronic Health Record data or other real-world healthcare data sources within life science companies, CROs, or healthcare organizations.
• Proficiency in SQL, R, and/or Python for statistical analysis, data manipulation, and visualization.
• Experience working with large, multi-domain healthcare datasets, including familiarity with distributed computing frameworks or scalable analysis techniques.
• Demonstrated eagerness to learn new programming languages, proprietary coding languages, or tools used for cohort building and data analysis.
• Strong understanding of real-world evidence principles, including bias, confounding, and study design considerations relevant to observational research.
• Proven ability to apply research methodologies such as cohort design, statistical modeling, and bias mitigation techniques to real-world data.
• Excellent communication skills, capable of delivering compelling product demonstrations and translating technical concepts for diverse audiences.
• Ability to manage multiple projects simultaneously in a fast-paced, startup environment while maintaining attention to detail and quality.
• Strong interpersonal skills with the ability to build credibility and trust with stakeholders at all levels, including technical teams and executive leadership.
• Self-motivated, proactive, and adaptable, with a passion for healthcare data and research innovation.

Nice to have

• Advanced degree (MS, MPH, PhD) in epidemiology, biostatistics, health economics, or a related field.
• Experience working with proprietary or specialized coding languages used in cohort building or data analysis.
• Familiarity with data privacy regulations and ITAR compliance related to healthcare data.
• Prior experience in a startup or rapidly evolving environment, demonstrating agility and flexibility.
• Knowledge of healthcare industry trends, regulatory considerations, and emerging research methodologies.

Skills & tools

• SQL
• R
• Python
• Distributed computing frameworks (e.g., Spark, Hadoop) (familiarity)
• Data visualization tools and techniques
• Data quality assessment and validation methods
• Strong analytical and problem-solving skills
• Excellent written and verbal communication skills

Practical notes

This role is based in Seattle, WA, and requires on-site presence. The position follows a hybrid work model, with in-person attendance required once a year for an onsite meeting. Candidates who can work remotely are eligible, but must be able to attend the annual onsite gathering. The role involves working closely with cross-functional teams, including data engineering, product management, and customer success, to deliver impactful solutions. The position offers an opportunity to contribute to innovative healthcare research initiatives, leveraging large-scale real-world data to support scientific discovery and improve patient outcomes.