Director, Marketing Analytics Lead

Bausch+Lomb Companies Inc.•Bridgewater, NJ

2d•$170,000 - $230,000•Hybrid

About The Position

We are seeking a forward-thinking and results-driven Director of Marketing Analytics to lead the strategy, design, and execution of our marketing measurement and analytics capabilities. This role will own the end-to-end analytics framework spanning Marketing Mix Modeling (MMM), Omnichannel Analytics, Campaign Measurement, Customer Segmentation, and Customer Lifetime Value (CLV), and will be a driving force behind transforming our traditional measurement framework into an Agentic AI-driven Marketing Analytics ecosystem. The Director will partner closely with Brand ECP/DTC leads, Media, Strategy, and Data Science teams to deliver actionable insights that enhance marketing ROI and accelerate business growth. Critically, this leader will champion the adoption of GenAI and agentic AI workflows to automate measurement, scale insight generation, and enable a new generation of always-on, self-serve marketing intelligence.

Requirements

Master's degree in Statistics, Data Science, Economics, Marketing, or a related quantitative field.
9+ years of experience in marketing analytics, with deep, hands-on expertise in Marketing Mix Modeling (both Linear and Bayesian approaches), Customer Segmentation, Customer Lifetime Value modeling, and Omnichannel measurement frameworks. Pharmaceutical or healthcare analytics experience strongly preferred.
Demonstrated passion for and experience driving AI-led innovation. Must show clear motivation to transform traditional marketing analytics into an Agentic AI-driven function, including hands-on use of modern AI assistants such as Claude and Codex to accelerate analytics, modeling, and insight delivery, and practical experience or strong vision for deploying GenAI, ML, and AI agents in measurement, optimization, and insight delivery workflows.
Deep, demonstrable understanding of marketing measurement frameworks, including Linear (traditional regression-based) and Bayesian MMM approaches, multi-touch attribution, incrementality, and experimental design. Familiarity with hierarchical models, priors specification, and modern probabilistic programming frameworks is highly valued.
Proficiency in Python, R, SAS, or comparable languages. Hands-on experience with Bayesian modeling libraries (e.g., PyMC, Stan, NumPyro), ML frameworks, and data visualization tools such as Power BI or Tableau. Familiarity with LLM-based and agentic frameworks (e.g., LangChain, agentic orchestration platforms) is a strong plus.
Strong analytical and problem-solving capabilities with a rigorous understanding of statistical and causal modeling techniques and their application to marketing decisions.
Excellent verbal and written communication skills, with the ability to translate complex modeling and AI concepts into clear, compelling narratives for non-technical and executive stakeholders.
Meticulous focus on data accuracy, methodological integrity, and reproducibility.
Proven ability to lead multiple complex analytics initiatives in parallel and deliver in a fast-paced, matrixed environment.
Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Responsibilities

Marketing Mix Modeling & Optimization: Design and operationalize advanced MMM frameworks, both Linear (traditional regression-based) and Bayesian, to quantify channel impact on leads, scripts, and priority KPIs. Translate statistical findings into budget optimization plans, scenario simulations, and forward-looking investment guidance. Lead efforts in evolving modeling methodology to incorporate hierarchical effects, adstock/saturation curves, and incrementality testing.
Omnichannel Analytics: Lead the measurement and optimization of integrated omnichannel marketing activity across HCP and consumer touchpoints, including digital, personal promotion, EHR, programmatic, social, email, and emerging channels. Build attribution and orchestration frameworks that quantify channel synergy, sequencing effects, and next-best-action opportunities. Support Brand Managers in delivering successful campaigns to drive brand priorities.
Customer Segmentation & Lifetime Value: Own the development, refresh, and activation of customer segmentation models (behavioral, value-based, needs-based, and predictive) across HCP and patient populations. Build and maintain Customer Lifetime Value (CLV) models that inform investment prioritization, NPP targeting strategy, and long-term portfolio planning.
Campaign Analytics & Measurement Framework: Manage the marketing tactic measurement framework, including Pilots, Brand Lift studies, A/B testing, and incrementality experiments. Establish standards for experimental design, holdout methodology, and statistical significance across the brand portfolio.
Agentic AI Transformation: Lead the transformation of marketing analytics from a report-driven function into an Agentic AI-driven capability. Champion the hands-on adoption of modern AI tools, including Claude, Codex, and other frontier LLM and agentic coding assistants, to accelerate analytics development, automate insight generation, and build autonomous AI agents that monitor performance, run diagnostics, recommend optimizations, and execute measurement workflows end-to-end. Partner with Data Science, IT, and AI/ML leadership to embed GenAI and agentic workflows across MMM, segmentation, campaign measurement, and omnichannel orchestration.
Marketing 360 Dashboard Ownership: Hold full end-to-end ownership of the Marketing 360 Dashboard, including its design, data pipelines, KPI definitions, governance, and evolution. Ensure the dashboard delivers a unified, trusted, and decision-grade view of marketing performance to Brand, Omnichannel, and Senior Leadership. Continuously elevate the dashboard from descriptive reporting into a predictive and prescriptive intelligence layer powered by AI agents.
Stakeholder Management: Partner closely with Media partners, Brand team, Marketing Hub and other stakeholders to translate business objectives into analytical roadmaps. Communicate insights and recommendations clearly to both technical and executive audiences and drive data-driven decision-making across the organization.
Team & Vendor Leadership: Lead the NPP Data Science team and partner with the Information Management (IM) team to manage marketing data assets across consumer and HCP promotional sources. Manage external analytics vendors and ensure delivery quality, methodological rigor, and alignment with internal standards.
Research & Innovation: Stay at the leading edge of marketing measurement, decision science, and AI/ML, including Bayesian methods, causal inference, agentic AI architectures, and large language model applications in analytics. Proactively pilot and scale innovations that meaningfully advance our measurement capabilities.