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About This Role
Job Description
Role Summary:
The Associate Director, US Marketing Engagement - HIV Prep will serve as a strategic analytics and insights partner to US HIV Prep Marketing. The role will translate complex patient, prescriber, market, access, and performance data into clear business insights that strengthen brand strategy, launch readiness, execution, and measurement. The successful candidate will combine strong healthcare data fluency, cross-functional leadership, and an understanding of HIV Prep dynamics.
Primary Responsibilities:
- Partner with US HIV Prep Marketing leaders to define key business questions, analytical priorities, success measures, and an integrated insights plan aligned with brand and portfolio objectives.
- Lead patient journey, market map, Prep dynamics, source-of-business, switching, adherence, persistence, HCP/account opportunity, segmentation, and early-adopter analyses.
- Develop launch and in-market KPI frameworks, tracking plans, dashboards, and decision-focused readouts that connect execution to business outcomes.
- Integrate patient, HCP, account, payer, geography, channel, and performance data into a coherent fact base, clearly communicating assumptions and limitations.
- Collaborate with Marketing, Market Research, Forecasting, Market Access, Data Strategy, Advanced Analytics, Finance, field-facing partners, and global teams.
- Translate analytical findings into concise executive narratives, recommendations, and actions; guide internal and external analytics partners and assure quality.
Data and Database Experience:
Hands-on familiarity with healthcare data and the judgment to match the right source to the business question are important. Relevant experience includes several of the following:
- IQVIA eLAAD or comparable longitudinal patient-level claims data, including cohort construction, Prep regimens, adherence, persistence, switching, and source-of-business analyses.
- Komodo Healthcare Map / Komodo claims or comparable open and closed claims assets for patient journey, HCP/HCO, referral, site-of-care, and longitudinal market analyses.
- IQVIA Xponent, DDD, NPA, NSP, PlanTrak, or similar prescription and subnational sales datasets for market sizing, trends, geographic analysis, HCP-level performance, and launch tracking.
- APLD, EMR, laboratory, payer, formulary, affiliation, specialty pharmacy, hub, consumer, media, and promotional datasets, as relevant.
- Data integration across patient, HCP, HCO, payer, product, geography, and campaign sources, with understanding linkage constraints, projection methodologies, refresh cadence, and data lag.
- SQL and large relational or cloud-based datasets; proficiency with Python, R, SAS, Databricks, Snowflake, Power BI, or Tableau is strongly valued.
HIV Prep Analytics Focus:
- People living with HIV population sizing, diagnosed and treated patient flows, Prep-naive and Prep-experienced cohorts, regimen dynamics, and unmet need.
- HCP and account opportunity assessment, prescribing behavior, patient mix, adoption, switching pathways, and segmentation activation.
- Launch readiness and performance tracking, including target population reach, adoption, persistence, and competitive dynamics.
Required Qualifications:
- Bachelor's degree in statistics, data science, epidemiology, health economics, business analytics, life sciences, engineering, or a related quantitative discipline.
- 5+ years of experience in pharmaceutical, biotechnology, healthcare, consulting, or healthcare-data analytics, with responsibility for commercial insights or marketing analytics
- Demonstrated experience using secondary healthcare data to answer strategic marketing questions and influence decisions
- Strong problem structuring, analytical interpretation, cross-functional leadership, stakeholder management, and executive communication skills
Preferred Qualifications:
- Master's degree or PhD in statistics, data science, epidemiology, health economics, public health, life sciences, business analytics, or a related quantitative discipline is desired.
- Experience applying AI, ML, and Generative AI capabilities to commercial pharmaceutical data, market engagement, omnichannel analytics, patient journey, access, or healthcare provider insights is strongly preferred
- Direct HIV Prep experience is desired; infectious disease, specialty medicine, or relevant launch experience is also valued.
- Deep experience with eLAAD, Komodo, Xponent, and related IQVIA datasets, including combining patient-level and prescription or sales data for a unified market view.
- Experience with launch analytics, patient journey, segmentation, market mapping, forecasting inputs, KPI design, digital measurement, and advanced analytics.
Leadership Capabilities:
- Strategic partner who connects analytics to brand and portfolio decisions.
- Enterprise collaborator who aligns functions and reduces fragmentation.
- Analytical translator who converts technical work into concise business recommendations.
- Quality and change leader who advances scalable, reproducible, and modern analytical practices.
Measures of Success:
- Marketing decisions are supported by a timely, trusted, and transparent analytical fact base.
- HIV Prep data and insights priorities are aligned to brand objectives.
- Analytical deliverables produce specific actions, not only descriptive reporting.
- Foundational datasets, definitions, and methods are consistent, documented, and reusable.
Required Skills:
Analytical Reports, Analytical Reports, Base SAS, Business Alignment, Business Analysis, Business Decisions, Business Intelligence (BI), Dashboard Development, Data Analysis, Database Design, Database Queries, Data Engineering, Data Modeling, Data Science, Data Visualization, Executive Leadership, Machine Learning (ML), Partner Relationship Management (PRM), Performance Dashboards, Problem Identification, Report Analysis, Software Development, Stakeholder Management, Stakeholder Relationship Management, Strategic Analysis {+ 4 more}
Preferred Skills:
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US and Puerto Rico Residents Only:
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
$156,900.00 - $247,000.00
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:
Domestic
VISA Sponsorship:
No
Travel Requirements:
10%
Flexible Work Arrangements:
Hybrid
Shift:
Not Indicated
Valid Driving License:
No
Hazardous Material(s):
n/a
Job Posting End Date:
10/12/2026*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: R418880
Salary Context
This $156K-$247K range is above the median for AI/ML Engineer roles in our dataset (median: $176K across 1540 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 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% 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 Required
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 $212,000 based on 11,857 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($201K) sits 5% below the category median. Disclosed range: $156K to $247K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Merck AI Hiring
Merck has 10 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Rahway, NJ, US, Rahway, NJ, North Wales, PA, US. Compensation range: $203K - $300K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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