Senior Associate, Health Economics and Outcome Research

KMK Consulting, Inc; India; On-site; INR 2,000,000 - 4,000,000; Full time

Job summary

KMK Consulting, Inc is seeking an experienced Health Economics & Outcomes Research (HEOR) Associate to lead observational database analytics and evidence synthesis with minimal supervision. You will consult on study design, data source identification, and methodology, and own RWE analyses using SAS/SQL/R/Python.

You will generate high quality deliverables, develop mock table shells, and ensure QC across analyses conducted by junior staff, while communicating findings to internal teams and

Qualifications

• MS in statistics, biostatistics, epidemiology, health economics and outcomes research, health policy, or similar.
• 4+ years hands-on experience in observational data studies including study design and statistical methodologies.
• Proficiency in SAS; SQL and R programming experience.
• Excellent interpersonal communication and study management skills.
• Ability to present HEOR findings to cross-functional teams in non-technical language.
• Comfort working in a dynamic, matrix environment.

Responsibilities

• Provide consultation and recommendations with clear business and statistical rationales on RWE studies/analyses.
• Lead and execute RWE studies/analyses using SAS/SQL/R/Python on claims, EMR, registries, etc.
• Generate high-quality deliverables (tables, graphs, study reports).
• Develop mock table shells, prepare specifications, and ensure QC on analyses by juniors.
• Track studies to meet timelines and manage stakeholder communications.

Skills

Interpersonal communication

Study management

Statistical reasoning

Microsoft Office

SAS

SQL

R programming

Python

Education

MS in statistics/biostatistics/epidemiology/HEOR/health economics

Health policy background

Tools

SAS

SQL

R

Python

Job description

Job Overview:

We are currently seeking an experiencedHealth Economics & Outcomes Research (HE&OR) 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 HE&OR 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

Technicalrequirements:

• Preferred MS in statistics, biostatistics, epidemiology, computer science, orother 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).