Research Scientist 2

Humana

2d•$78,400 - $107,800•Remote

About The Position

The Research Scientist 2 is part of Humana’s Quality & Cost Strategy Analytics team, which supports performance management and evaluation of clinical programs. The role applies statistical, epidemiologic, and analytical methods to healthcare data to evaluate clinical program performance, understand outcome drivers, and support clinical and business decision-making. The scientist designs and executes outcomes studies, conducts deep-dive analyses to diagnose performance, and translates findings into recommendations for clinical, operational, and business partners. The position requires strong analytical thinking and attention to detail, and the ability to independently address moderately complex questions while seeking guidance on more complex or ambiguous methodological issues. The team works across clinical strategy, analytics, and enterprise value, applying research and performance measurement to identify opportunities, evaluate clinical solutions, and support high-value care and continuous program improvement. This is a remote position. Occasional travel to Humana offices for training or meetings may be required. Employees working from home must have internet service with at least 25 Mbps download and 10 Mbps upload speed, and work from a dedicated space that protects member PHI/HIPAA information. The position is scheduled for 40 hours per week and is not eligible for work visa sponsorship.

Requirements

Master’s degree or PhD in Epidemiology, Biostatistics, Economics, Statistics, Health Services Research, Clinical Informatics, or a related quantitative discipline.
At least 2 years of experience applying statistical, epidemiologic, econometric, or related quantitative methods to large, complex datasets.
Strong foundation in causal inference and study design, including observational studies, comparative effectiveness research, and randomized controlled trials.
Experience manipulating and analyzing data using Python, PySpark, R, SAS, or comparable analytical tools.
Strong analytical thinking and structured problem-solving skills, including the ability to translate clinical and business questions into analytical approaches.
Ability to select and apply appropriate methodologies to moderately complex research and business questions, seeking guidance on more complex methodological challenges.
Excellent written and verbal communication skills, including synthesizing complex methods and findings into clear insights and recommendations for non-technical audiences.
Strong attention to detail and organizational skills, with the ability to manage multiple priorities.
Ability to work independently and collaborate with multidisciplinary and cross-functional teams.
Strong interest in healthcare and a passion for improving health outcomes and healthcare value.

Nice To Haves

Experience in health insurance, managed care, healthcare analytics, or health services research.
Strong understanding of healthcare payer economics, including utilization, medical cost, and total cost of care.
Experience with medical claims, pharmacy claims, laboratory data, eligibility/enrollment data, and clinical program operational data.
Familiarity with clinical concepts in chronic and specialty conditions, such as cardiology, chronic kidney disease, oncology, or other high-cost conditions.
Experience evaluating clinical programs, care management interventions, or value-based healthcare initiatives.
Familiarity with advanced causal inference and causal machine learning techniques, such as double/debiased machine learning, doubly robust estimation, and meta-learners.
Proficiency in Python and PySpark, with experience working in Databricks and Microsoft Azure.

Responsibilities

Design and execute outcomes studies evaluating the clinical, utilization, and financial performance of clinical programs using observational and experimental methods.
Apply causal inference, epidemiologic, and statistical methods to estimate program impact and generate evidence for decision-making.
Analyze medical and pharmacy claims, enrollment, and operational data to identify performance drivers, diagnose gaps, and uncover improvement opportunities.
Translate clinical and business questions into defined analytical questions and hypotheses, partnering with senior scientists as needed on complex study designs and methods.
Partner with clinical, operational, financial, and business stakeholders to turn analytical insights into recommendations for clinical strategy, program design, contracting, and performance improvement.
Develop analytical reports, presentations, and executive-level readouts for internal and external stakeholders.
Communicate complex methodologies and findings, including their implications and limitations, as actionable insights for technical and non-technical audiences.
Determine appropriate analytical approaches and make methodological decisions in complex or ambiguous situations.
Manage multiple analytical priorities while maintaining methodological rigor, accuracy, and reproducibility.