Associate Principal Scientist/Associate Director - Real World Evidence & Data Sc

Job Description

We are seeking a highly skilled and motivated Associate Principal Scientist/Associate Director with expertise in conducting outcome researching using real world data, as well as building supervised and unsupervised machine learning models. 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 and Interpretation:

• 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.

Unstructured Clinical Data:

• Utilize transfer learning, fine tuning, GAN, transformer, attention, auto encoder, and other advanced neural network techniques in building machine learning model. Implement algorithms for unstructured data including but not limited to X-ray, CT, MRI, ECG signal, ECOH diagram.

Collaboration And Communication:

• Work closely with stakeholders in research, business, and IT functions to provide data-driven insights and solutions.

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.

Education Requirement:

• An advanced degree (MA/MS, PhD, ScD etc.) in a quantitative field such as statistics, biostatistics, data science, biomedical informatics, health informatics, clinical informatics, epidemiology, health economics, biometrics, operations research, engineering, computer science or similar fields.

Skills Requirements:

• Strong machine learning programming skills in Python, strong statistical programming skills using R or SAS

• Solid understanding proficiency in using machine learning frameworks (e.g., TensorFlow, PyTorch, OpenCV, Scikit-learn, Hugging Face, etc.)

• Broad and in-depth hands-on professional experience and knowledge of RWD such as administrative claims, EHR/EMR, patient registry, and public-use databases, to generate RWE is required.

• Experience identifying research cohort of interest using disease, procedure, therapeutic classification codes such as ICD-9-CM, ICD-10-CM, SNOMED, LOINC, NDC, HCPCS, CPT, etc., is required.

• Good interpersonal communication and organizational skills with strong attention to detail, clarity, accuracy, and conciseness is required.

• Ability to plan, organize, and work on multiple analytics tasks simultaneously in different but interrelated therapeutic areas is required.

Experience Requirements:

• Master’s degree in a related field with at least 5 years post-graduate experience conducting real world healthcare data research

• Doctoral degree in a related field with at least 3 years post-graduate experience conducting real world healthcare data research.

Preferred Experience and Skills:

• Foundational understanding of statistical and machine learning terminology, concepts and techniques in real world data is preferred.

• Experience with outcomes research, including RWE studies, throughout the product lifecycle within biomedical research and/or healthcare organization is preferred.

• Research experience in using LLMs on clinical data (BioBERT, MedBERT, etc.)

• Familiarity with Generative AI and prompt engineering

• Co-authored peer-reviewed publications that utilized data science methods, and/or dedicated to datathon, hackathon, Kaggle, or other competitions (recommend adding bibliographic records, url to competition leaderboard, and GitHub repository in the Resume/CV)

Current Employees apply HERE

Current Contingent Workers apply HERE

US and Puerto Rico Residents Only:

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U.S. Hybrid Work Model

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.This Hybrid work model does not apply to, and daily in-person attendance is required for, field-based positions; facility-based, manufacturing-based, or research-based positions where the work to be performed is located at a Company site; positions covered by a collective-bargaining agreement (unless the agreement provides for hybrid work); or any other position for which the Company has determined the job requirements cannot be reasonably met working remotely. Please note, this Hybrid work model guidance also does not apply to roles that have been designated as “remote”.

The Company is required to provide a reasonable estimate of the salary range for this job in certain states and cities within the United States. Final determinations with respect to salary will take into account a number of factors, which may include, but not be limited to the primary work location and the chosen candidate’s relevant skills, experience, and education.

Expected US salary range:

Available benefits include bonus eligibility, long term incentive if applicable, health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and sick days. A summary of benefits is listedhere.

San Francisco Residents Only: We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance

Los Angeles Residents Only: We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance

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Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.

Employee Status:

Regular

Relocation: