Director - Data Science (RGM)

About the Role

We are looking for a seasoned Director – Data Science to help build and scale our next-generation Revenue Growth Management (RGM) practice, combining deep expertise in Data Science, advanced analytics, commercial decision-making, and large-scale program delivery.

The ideal candidate will have deep experience applying advanced analytics and data science across multiple RGM levers such as Pricing, Promotion, Assortment, and Trade Planning/Trade Investment Management, and will be responsible for driving enterprise-scale solutions for global clients across CPG, Retail, Healthcare & Life Sciences, and Travel & Hospitality.

The focus is on building decision intelligence platforms, scalable RGM solutions, AI-powered products, and commercial transformation programs within our existing Data Science leadership expectations while bringing strong domain depth.

Key Responsibilities

Revenue Growth Management & Data Science Leadership

· Lead end-to-end execution of advanced analytics, AI, and Data Science programs across multiple RGM domains:

o Pricing & Price Optimization

o Price Elasticity Modeling

o Trade Promotion Optimization (TPO)

o Assortment Optimization

o Trade Investment Effectiveness

o Revenue Planning & Forecasting

o Consumer & Commercial Analytics

· Design and implement enterprise-grade RGM solutions that integrate multiple commercial levers rather than isolated analytics engagements.

· Drive the development of scalable Decision Intelligence systems that support commercial decision-making.

· Apply advanced statistics, machine learning, optimization, forecasting, causal analytics, and AI techniques to solve complex revenue growth challenges.

· Establish best practices for model development, validation, deployment, and business adoption.

Solution Development & Innovation

· Build and scale enterprise RGM platforms and AI-powered commercial solutions.

· Drive adoption of GenAI and Agentic AI capabilities within commercial and RGM ecosystems.

· Develop reusable accelerators, frameworks, and solution assets across RGM domains.

· Partner with industry and practice leaders to create differentiated offerings for clients.

Client Advisory & Commercial Consulting

· Act as a trusted advisor to client stakeholders and executive leadership.

· Lead solution workshops, value discovery discussions, and transformation roadmaps.

· Translate business problems into analytics and AI-driven solutions.

· Communicate complex analytical insights and solution approaches to both technical and non-technical audiences.

Project & Program Leadership

· Oversee project delivery timelines, quality metrics, commercial outcomes, and delivery governance.

· Manage large-scale analytics and AI engagements across global clients.

· Act as the bridge between business stakeholders, domain experts, data scientists, and engineering teams.

· Identify and mitigate project risks while ensuring alignment with business objectives.

Practice Building & Pre-Sales

· Contribute to business development, solutioning, proposals, RFPs, and strategic pursuits.

· Support growth of the RGM practice through thought leadership and capability development.

· Build relationships across clients, industry leaders, and ecosystem partners.

· Drive innovation initiatives and contribute to the development of future-state RGM offerings.

Team Leadership

· Lead and mentor teams of data scientists, data engineers, consultants, and analysts.

· Foster a culture of innovation, collaboration, and continuous learning.

· Develop future leaders and strengthen organizational capabilities in RGM and Data Science.

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Required Qualifications

· 15–20 years of overall experience with significant experience in Data Science, Analytics, and Commercial Transformation.

· At least 8–10 years of experience leading advanced analytics and Data Science programs.

· Strong domain expertise across two or more RGM levers, including:

o Pricing

o Promotion / Trade Promotion Optimization

o Assortment Optimization

o Trade Planning / Trade Investment Management

· Proven experience delivering enterprise-scale analytics and AI solutions in commercial functions.

· Strong understanding of internal and external data ecosystems used within RGM.

· Hands-on expertise in machine learning, statistical modeling, optimization, forecasting, and AI-driven decision-making.

· Deep technical expertise in processing and analyzing large-scale time series, syndicated, POS, shipment, pricing, promotion, and trade investment data.

· Strong quantitative foundation in regression, regularization, causal inference, forecasting, hierarchical Bayesian modeling, and model diagnostics for commercial analytics use cases.

· Hands-on experience solving complex optimization problems, including MILP, MINLP, constrained optimization, simulation, scenario planning, and trade-off analysis.

· Practical expertise with open-source and commercial optimization solvers and scalable implementation approaches for computationally intensive workloads.

· Ability to evaluate RGM models using both technical metrics and business outcomes, including elasticity quality, forecast accuracy, promotion lift, halo, cannibalization, demand transference, margin, revenue, and ROI impact.

· Experience with Python, R, SQL, and modern analytics ecosystems.

· Strong MLOps and productionization experience, including distributed computing, model monitoring, retraining, governance, reproducibility, and deployment of large-scale analytics pipelines.

· Demonstrated leadership managing large teams and complex client engagements.

· Strong client-facing, consulting, and stakeholder management experience.

· Advanced degree in Data Science, Statistics, Mathematics, Economics, Operations Research, Computer Science, Engineering, or related field.

Key Differentiator

This role offers the opportunity to build the future of Revenue Growth Management by combining RGM expertise, Data Science, AI/ML, GenAI, and Decision Intelligence to create enterprise-scale solutions that transform how commercial decisions are made. Candidates should have demonstrated Data Science experience across multiple RGM levers (at least two of Pricing, Promotion, Assortment, or Trade Planning).