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Job Description
Job Description
The Senior Specialist, US Market Engagement (USME) will be responsible for developing and communicating data\-driven and actionable insights that drive greater customer and market understanding to inform brand strategy, help meet in\-line brand growth and commercial objectives.
This hybrid role requires the individual to be a key partner to the US Vaccines Marketing Team, supporting analytics execution across the portfolio (Adolescent, Adult, and Ecosystem). This person will be business facing and will “connect the dots” across the broader DHH capability ecosystem, partnering closely with teams in market research, forecasting, payer insights \& analytics, data science, data strategy, and data solutions.
The preferred candidate should have intellectual curiosity, an entrepreneurial spirit, a consultative mindset, and a strong understanding of healthcare \& pharma marketing. The person should be able to identify the data, analytics, and research needs to define, enable, and inform commercial strategies of our brand and business leaders. The candidate will have a growth mindset, embody a culture of continuous learning, and possess strong technical and communication skills.
Primary Job Function and Key Responsibilities
Stakeholder Partnership: Thoroughly appreciate the assigned internal stakeholder business needs and priorities to help build analyses promoting business objectives by delivering actionable insights.
Analytic Accountabilities: Be accountable for ensuring delivery of analyses with high quality standards, timeliness, compliance, and excellent user experience (routinely keeping stakeholders and USME leads updated on progress).
Data Mining \& Analytics Execution: Mine and analyze data leveraging advanced analytical/statistical techniques from disparate databases/sources (claims data/EMR Data/Sales/Distributions and other commercial sources) to drive optimization and improvement of therapy area commercial strategies.
Capability Ownership: Connect the dots across various commercial capabilities (e.g., dashboards, MMx, MarTech capabilities etc) to synthesize cohesive insights and actively inform platform/capability enhancements that directly align with evolving Marketing team needs.
AI Innovation, Automation, \& Digital Mastery: Demonstrate strong interest, baseline mastery, or a proactive willingness to learn next\-generation technologies (specifically Generative AI, agentic workflows, and LLMs). Actively identify, pilot, and champion the integration of AI\-driven automation to streamline routine reporting, automate data narratives, and drive efficiency within a regulated environment (complying with data privacy and compliance guidelines).
Advanced Methodologies \& Innovative Experimentation: Convey new trends and analytical methodologies being implemented/considered within the company ecosystem and bring new ideas forward that enhance the analytic capabilities of the organization. Contribute directly to innovative experiments, idea generation, and incubation, identifying tangible and measurable criteria to improve business processes and strategies.
Influence \& Communication: Effectively convey analyses and positively influence stakeholders, supporting the USME team by translating data into actionable commercial stories and co\-presenting performance readouts to marketing leadership.
Education Requirements
A minimum of a BS (or equivalent) in Marketing, Business Strategy, Business Consulting, Data Science, Computer Science, Statistics, Mathematics, Decision Science, Economics, Engineering, Public Health, or an equivalent scientific/commercial discipline.
An MBA, Master’s, or Doctorate degree in a highly quantitative or commercial discipline is a plus.
Required Experience \& Skills
Pharma Analytics: Minimum of 3 plus years of relevant knowledge using data science and/or analytical techniques to deliver measurable impact in the commercial pharma landscape.
Pharma Data Assets: Knowledge in mining medical claims/EMR, social media, etc. data with a strategic/inquisitive mindset and a proven record of being able to produce actionable business insights that drive positive commercial results.
Database \& Query Skills: Ability to extract data from various database tables using tools such as SQL, Databricks, Dataiku to develop features and datasets to be used in commercial analysis.
Effective Storytelling: Strong communication skills using effective storytelling grounded on data insights.
Methodological Awareness: Ability to provide guidance and help define tactics and strategies to implement targeting and segmentation schemes using predictive and machine learning models.
Presentation Formulation: Comfort formulating actionable insights and recommendations from commercial analytics into presentations (using PowerPoint etc.) and co\-presenting results to various levels of franchise management.
Pharma Industry Knowledge: Proven knowledge of business processes and industry/market trends within the pharmaceutical/healthcare space.
Matrix Navigation: Effective organizational and project management skills to navigate a complex matrix environment and organize/prioritize work efficiently and effectively.
Tech\-Forward Mindset: Openness and motivation to build skills in AI, machine learning, and automation (specifically learning how agentic AI and automated pipelines can enhance commercial analytics and reporting).
Work Location
Location: Upper Gwynedd, PA or Rahway, NJ.
Model: Hybrid (expected to be in the office at least 3 days/week, Monday through Thursday).
Core Required Skills
Business Analysis, Data Analytics, Data Science, Data Visualization, Stakeholder Relationship Management, Strategic Planning, Requirements Management, Innovation, Artificial Intelligence (AI) Adoption
Required Skills:
Brand Growth, Brand Strategy, Business Intelligence (BI), Business Strategies, Commercial Analytics, Commercial Strategies, Computer Science, Continuous Learning, Database Design, Data Engineering, Data Modeling, Data Science, Data Visualization, Infectious Disease, Machine Learning (ML), Market Research, Project Management, Software Development, Stakeholder Relationship Management, Strategic Management, Strategic Planning, Waterfall Model
Preferred Skills:
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Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities. Please click here if you need an accommodation during the application or hiring process.
As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristics. As a federal contractor, we comply with all affirmative action requirements for protected veterans and individuals with disabilities. For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit:
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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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The salary range for this role is
$129,000\.00 \- $203,100\.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.
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
Search Firm Representatives Please Read Carefully
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:
VISA Sponsorship:
Travel Requirements:
Flexible Work Arrangements:
Hybrid
Shift:
Valid Driving License:
Hazardous Material(s):
Job Posting End Date:
08/21/2026\*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.
Requisition ID: R410881
Salary Context
This $129K-$203K range is below the median for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Merck, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($166K) sits 23% below the category median. Disclosed range: $129K to $203K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Merck AI Hiring
Merck has 5 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer. Based in Rahway, NJ, US. Compensation range: $137K - $331K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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