Associate Principal Scientist/Associate Director, Real World Evidence Full-time NEW

Associate Principal Scientist/Associate Director

We are seeking a highly skilled and motivated Associate Principal Scientist/Associate Director with expertise in conducting outcome research using real world data. This role requires the ability to analyze complex data sets, develop algorithms, and create innovative solutions to enhance our data-driven decision-making processes.

Key Responsibilities:

Real World Data Analysis:

Analyze and interpret large volumes of structured and unstructured real-world patient level healthcare data, including but not limited to administrative claims, EHR/EMR, disease registry, and public-use databases. Develop machine learning algorithms and statistical/survival analysis models to extract meaningful insights and outcome research evidence.

Collaboration And Communication:

Work closely with stakeholders in outcome research, medical affairs, statistical programming, and IT functions to provide data-driven insights and solutions. Provide data science and real-world data expert inputs in internal and external collaborations. Present research findings in internal and external scientific congress meetings.

Project Management:

Independently lead Real-World Evidence outcome research or advanced AI/machine learning research projects with minimum supervision.

Continuous Learning and Innovation:

Stay current with the latest research and technologies in data science and machine learning. Proactively seek opportunities to improve existing processes and methodologies.

Qualifications:

Required Skills & Qualifications

• Proficiency in Machine Learning and Statistical Programming using tools such as R, SAS, or Python, with a strong foundation in model development and data analysis.

• Advanced SQL skills for efficient data querying, manipulation, and transaction management across complex datasets.

• Extensive hands-on experience with Real-World Data (RWD) sources including administrative claims, EHR/EMR systems, patient registries, and public-use databases, with a proven track record of generating Real-World Evidence (RWE).

• Expertise in cohort identification using clinical and therapeutic classification codes such as ICD-9-CM, ICD-10-CM, SNOMED, LOINC, NDC, HCPCS, and CPT.

• Experience in developing study protocols for non-interventional and methodological research studies, including observational and retrospective designs.

• Working knowledge of research project operations, including contracting, procurement, and budget management processes.

• Strong interpersonal and communication skills, with a keen attention to detail, clarity, and precision in documentation and collaboration.

• Ability to manage multiple analytical projects simultaneously, often across diverse therapeutic areas, with effective planning and organizational skills.

Education & Professional Experience

• Master's degree in a relevant field (e.g., Epidemiology, Biostatistics, Public Health, Data Science) with a minimum of 5 years of post-graduate experience conducting research using real-world healthcare data.

• Doctoral degree (PhD, ScD, DrPH) in a related discipline with at least 2 years of post-graduate experience in real-world healthcare data research.

Preferred Experience & Skills

• Strong foundational knowledge of statistical and machine learning concepts, with practical application in real-world healthcare data contexts.

• Proven experience leading Real-World Evidence (RWE) studies within biomedical research or healthcare organizations.

• Experience of implementing outcome research studies in following disease and therapeutical areas – heart failure, PAH, COPD, IBD, Ophthalmology

• Hands-on experience applying large language models (LLMs) such as BioBERT, MedBERT, or similar, to clinical data for research purposes.

• Demonstrated ability to mentor and support junior team members, fostering growth and collaboration within research teams.

• Co-authorship of peer-reviewed publications involving data science methodologies, and/or active participation in data-focused competitions such as datathons, hackathons, or Kaggle challenges—ideally centered on real-world healthcare data.

Required Skills: Accountability, Clinical Data, Computer Science, Electronic Health Records (EHR), Electronic Medical Records Management, Health Sciences, Large Language Models (LLMs), Machine Learning, Multi-Management, Ophthalmology, Outcomes Research, Scientific Research, SNOMED CT, Statistical Analysis, Statistical Programming, Statistics, Strategic Procurement, Structured Query Language (SQL), Survival Analysis, Transaction Management

Preferred Skills: Database Systems, Python (Programming Language), R Programming, Statistical Analysis Systems (SAS) Programming

Salary range for this role is $139,600.00 – $219,700.00. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee's position within the salary range will be based on several factors including, but not limited to relevant education, qualifications, certifications, experience, skills, geographic location, government requirements, and business or organizational needs.

The successful candidate will be eligible for annual bonus and long-term incentive, if applicable.

We offer a comprehensive package of benefits. Available benefits include medical, dental, vision healthcare and other insurance benefits (for employee and family), retirement benefits, including 401(k), paid holidays, vacation, and compassionate and sick days. More information about benefits is available at https://jobs.merck.com/us/en/compensation-and-benefits.

You can apply for this role through https://jobs.merck.com/us/en (or via the Workday Jobs Hub if you are a current employee). The application deadline for this position is stated on this posting.

We are proud to be a company that embraces the value of bringing together talented, and committed people with diverse experiences, perspectives, skills and backgrounds. The fastest way to breakthrough innovation is when people with diverse ideas, broad experiences, backgrounds, and skills come together in an inclusive environment. We encourage our colleagues to respectfully challenge one another's thinking and approach problems collectively.

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Effective September 5, 2023, employees in office-based positions in the U.S. will be working a Hybrid work consisting of three total days on-site per week, Monday – Thursday, although the specific days may vary by site or organization, with Friday designated as a remote-working day, unless business critical tasks require an on-site presence.

The application deadline for this position is stated on this posting.