Sr Associate, Health Economics and Outcome Research

KMK Consulting; Hyderabad; On-site; INR 1,500,000 - 2,300,000; Full time

Job summary

KMK Consulting Inc. in Hyderabad, India is seeking an experienced HEOR Associate to oversee the scientific and methodological aspects of observational database analytics and evidence synthesis with minimal supervision.

You will lead and execute RWE studies using SAS/SQL/R/Python across claim, EMR, registry data and public datasets, deliver interpretable outputs, and ensure QA and timely delivery while contributing to ongoing education in RWE methods.

Qualifications

• MS or higher in statistics, biostatistics, epidemiology, health economics, or related fields.
• At least 4 years hands-on experience in observational data studies.
• Proficiency in SAS; SQL and R; Python is a plus.
• Excellent interpersonal communication and study management skills.
• Ability to present HEOR results clearly to cross-functional teams.
• Experience working in matrix environments.
• Strong MS Office skills.

Responsibilities

• Consult with clients and internal teams on study design and methodology.
• Lead RWE studies using SAS/SQL/R/Python on claim, EMR, registry data.
• Generate data tables, graphs, and study reports.
• Develop mock table shells and ensure QC on analyses.
• Manage timelines and communicate project status.
• Present findings internally and externally when appropriate.
• Stay current with latest HEOR methodologies.
• Support education of relevant teams on RWE methods.

Skills

SAS programming

SQL

R

Python

Statistical methods

Data interpretation

Communication

Project management

Education

MS in statistics/biostatistics/epidemiology/health economics

MS in health economics

Tools

Excel

PowerPoint

Job description

Job Overview:

We are currently seeking an experienced Health Economics Outcomes Research (HEOR) Associate. This position is responsible for the scientific and methodological aspects of all observational database analytics and evidence synthesis with minimal supervision.

Job Description

• Provide consultation and recommendations with clear business and statistical rationales to clients and internal team on all aspects of RWE databases studies/analyses including objectives, study design and methodology, data source identification and comparison, protocol development, statistical analysis and interpretation.
• Lead and execute with full ownership of RWE studies/analyses by SAS/SQL/R/Python based on claim database, EMR database, registry data and public used files.
• Generate high quality, readily interpretable deliverables (e.g., data tables, graphs, charts, study reports)
• Design and develop mock table shells, prepare specifications, and ensure quality control on analyses conducted by junior level associates.
• Effectively manage and track all studies/analyses to ensure timelines are met and all stakeholders aware of project status. Foresee potential issues and impact on project timeline, and provide suggestions on best path forward for engagement success.
• Effectively communicate research findings internally and externally, as appropriate (e.g., congresses, publications)
• Ensure latest methodologies and analytical techniques are implemented.
• Contribute to the continuing education of relevant line functions on RWE methodologies.

Requirements

• Minimum MS in statistics, biostatistics, epidemiology, health economics and outcomes research, health policy, or similar.
• At least 4 years hands‑on experience in observational data studies including study design and statistical methodologies.
• Professional programming skills with SAS. SQL and R programming experience.
• Excellent interpersonal communication and study management skills.
• Ability to take detailed HEOR study results and communicate them in a clear, non‑technical manner to internal cross‑functional teams, using language that resonates with the teams, while maintaining the integrity of key findings.
• Ability to work effectively in a constantly changing, diverse, and matrix environment.
• Ability to proactively identify new opportunities and solutions
• Strong working knowledge of the Microsoft Office Suite (Word, PowerPoint, Excel)

Qualifications:

• Positive attitude/interested: Good candidates care about the result and how the result be used. They are willing to spend more time to explore more in addition to what is requested. They are able to readily take ownership of responsibilities
• Good problem‑solving/critical thinking skills: Good candidates are able to understand problems clearly. They ask the right questions, break problems down into hypotheses and propose solutions in a coherent manner.
• Solid programming and analytical skills: Good candidates demonstrate competence in the application of statistical techniques and professional in programming which includes good programming habit and self‑QC process.
• Good communication skills: Good candidates are able to take detailed study results and communicate them in a clear, non‑technical manner to internal cross‑functional teams, using language that resonates with the teams, while maintaining the integrity of key findings.
• Great at time and task management: Good candidates are able to estimate the amount of time needed to complete a task, communicate this to client clearly and deliver it on time.
• Quick learning capability/Self‑motivated: Good candidates have the ability to learn new technologies on their own.
• Good team player

Technical requirements:

• Preferred MS in statistics, biostatistics, epidemiology, computer science, or other quantitative analysis fields.
• Demonstrated competence in the application of statistical techniques, such as hypothesis testing, regression analysis, machine learning, etc..
• Professional programming skills with SAS and SQL. R and/or Python programming experience is plus.
• Strong working knowledge of the Microsoft Office Suite (Word, PowerPoint, Excel).