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The Opportunity Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. Youll work at the heart of global teams across Advisory, Assurance, Tax and Business Servicessolving real client challenges through connected collaboration. Well help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a differenceevery day. sign, KPI framework definition, model operationalization, and integration with TPM/ERP systems. Establish analytical standards, reusable model components, and governance controls (lineage, auditability, explainability) across data science workstreams. Drive AI/ML use case identification, feasibility scoping, and delivery for commercial analytics contexts including promotional ROI prediction, demand sensing, and fund effectiveness scoring. Ensure analytical outputs are accurate, defensible, and translated into actionable commercial recommendations for client leadership. Client Engagement & Advisory Engage directly with senior client stakeholdersCDO, VP Finance, Trade Marketing, Sales Opsto present analytical findings, explain model assumptions, and align on commercial implications. Shape and co-develop the client's RGM analytical roadmap: from baseline trade spend analytics through advanced optimization and AI-assisted decision support. Advise on organizational design for analytics-enabled NRM functions: KPI ownership, insight cadences, and decision governance. Contribute to business development through PoV development, proposal inputs, and RFP response support for RGM/TPM analytics pursuits. Data Engineering & Platform Oversight Oversee construction of analytical data pipelines from SAP, Salesforce, and other enterprise systems to consumption layers. Govern data quality controls: profiling, cleansing, hierarchy reconciliation (customer/product master, UoM, time-series), and reconciliation against source systems. Establish and enforce standards for data model documentation, pipeline governance, and version control across analytical workstreams. Collaborate with client data engineering and IT teams on platform integration, access controls, and analytical environment management. Team Leadership & Talent Development Lead and mentor a team of Senior Associates, Associates, and Analysts; enforce analytical rigor, delivery discipline, and documentation standards. Provide effort estimation, planning inputs, and WBS/story sizing for analytics and data science workstreams. Act as primary technical escalation point for modeling, data, and platform challenges. Support recruitment, onboarding, and capability building for the PPRM analytics talent pool. Candidates should demonstrate substantial experience and/or knowledge in any sector in the following areas: Trade Promotions Management: End-to-end TPM lifecycle fluencyMaster Data, Funds Management, Volume Planning, Promotion Planning, Optimization, Accruals, Payments, Post Event Analytics, Reportingwith platform exposure (Salesforce CG Cloud, SAP TPM, or equivalent). Revenue Growth Management: Deep understanding of RGM frameworks: price-volume-mix, T/S ratio, net revenue waterfall, category and channel profitability, fund structure, and baseline vs. incremental volume methodology. Data Science & Machine Learning: Strong applied ML background in commercial contextsforecasting, segmentation, elasticity, anomaly detection, causal inference for promotional uplift. Analytics Platform Architecture: Experience designing and governing analytical environments integrating TPM/ERP data sources with consumption layers (BI, ML pipelines, dashboards). AI-Enabled Commercial Analytics: Track record of operationalizing AI/ML outputs in RGM/TPM contexts with appropriate governance, explainability, and auditability. Candidates should be able to demonstrate extensive management consulting and data science leadership abilities that include the following: Data Science & Quantitative Modeling 811 years of total experience, with at least 45 years in data science, advanced analytics, or quantitative modeling roles in commercial/RGM/TPM contexts. Advanced proficiency in Python (pandas, scikit-learn, statsmodels, XGBoost, Prophet, or similar) and/or R for model development, validation, and productionization. Experience designing and delivering trade promotion ROI models, baseline volume forecasting, promotional uplift attribution, price elasticity estimation, and customer segmentation models at enterprise scale. .