Note: The job is a remote job and is open to candidates in USA. Truveta is hiring a Customer Facing Research Analyst to help life sciences partners turn research questions into rigorous analyses using real-world EHR data. The role combines customer guidance, research methodology, analytics, and technical support to deliver studies and advance customer research.

Responsibilities

• Partner closely with life sciences customers to understand research questions and translate them into analytical approaches
• Required to excel in providing technical analytics support as well as directly working with customers on calls to troubleshooting customer analysis
• Use technical skills to scope out customer analyses requests, produce studies and results using SQL, R and Python within an agreed upon deadline
• Build strong, trusted relationships with customer stakeholders, acting as a key partner in advancing their research goals
• Apply appropriate research methodologies, including cohort design, bias mitigation, and statistical analysis
• Communicate on the status of various projects and collaborate with success managers to ensure that Truveta clients can be successful with the platform
• Guide customers on best practices in real-world data research, including study design tradeoffs and interpretation of results
• Lead customer-facing discussions to unblock research challenges and drive projects forward
• Collaborate with customers to support peer-reviewed publications and high-quality research outputs
• Deliver both rapid-response analyses and deeper, in-depth investigations depending on customer needs
• Provide technical support and troubleshooting for customer analyses, code, and notebooks
• Create enablement materials as the Truveta platform evolves to help onboard new researchers to our increasing capabilities
• Collaborate cross-functionally to investigate data quality and demonstrate data reliability
• Deliver feedback to internal teams based on customer requests to inform Truveta’s product roadmap

Skills

• Undergraduate or graduate degree in clinical research, epidemiology, biostatistics, data science, clinical informatics, or a related field
• 5+ years of experience working in a technical customer-facing role, delivering high-quality research studies & analyses
• 3+ years of experience wrangling and analyzing Electronic Health Record data or other Real World Data sources in life science companies, CROs, other EHR data companies or healthcare organizations
• Strong proficiency in SQL, R and/or Python for statistical analysis
• Experience working across large, multi-domain healthcare datasets with millions of patients and hundreds of millions of records, leveraging distributed computing frameworks for scalable analysis
• Willingness to learn new coding languages including internal proprietary coding language to analyze data and build cohorts
• Strong understanding of real-world evidence principles, including bias, confounding, and study design considerations
• Demonstrated experience applying research methodologies, including cohort design and statistical approaches
• Experience delivering high-quality product demonstrations that enable customers or stakeholders to understand and effectively leverage data, platform capabilities, and analytical workflows
• Proven ability to learn, adapt, and independently drive multiple projects forward in a fast-paced, start-up environment
• Strong executive presence with the ability to build credibility and trust across stakeholders and effectively communicate complex technical concepts to both executive and technical audiences
• Please note that all applicants must be authorized to work in the United States for any employer as we are unable to sponsor work visas or permits (e.g. F-1 OPT, H1-B) at this time
• Advanced degree (MS, MPH, PhD) in epidemiology, biostatistics, health economics, or related field
• Experience supporting or contributing to peer-reviewed publications or conference abstracts
• Knowledge of advanced statistical methods such as regression, propensity score methods, survival analysis, and longitudinal data analysis
• Experience applying methods for causal inference or handling incomplete data in observational research
• Experience with Spark/PySpark or distributed data processing
• Experience with Regression, Propensity Score Matching, Kaplan-Meier Analyses, or Survival Analyses
• Experience working in customer-facing or consulting-style roles
• Demonstrated ability to present research findings to both technical and non-technical audiences

Benefits

• Hybrid model and working from anywhere; in-person attendance is required at least once per year for an onsite meeting.
• Comprehensive benefits with strong medical, dental and vision insurance plans
• 401K plan
• Professional development & training opportunities for continuous learning
• Work/life autonomy via flexible work hours and flexible paid time off
• Generous parental leave
• Regular team activities (virtual and in-person)
• Eligible for stock options

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