TPM + RGM Data Scientist - Senior Associate

Industry/Sector

Not Applicable

Specialism

Customer

Management Level

Senior Associate

Job Description & Summary

The Opportunity

Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll 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 difference—every day.

As a TPM + RGM Data Scientist - Senior Associate, you will engage with clients to enhance their pricing and profitability strategies within our Customer practice. This role involves analyzing complex data to provide insights that drive customer-centric solutions. As a Senior Associate, you will leverage your skills to build meaningful client relationships and navigate complex challenges. You will guide and mentor junior team members, fostering a collaborative environment that encourages growth and development.

In this role at PwC Acceleration Center India, you will be part of a dynamic team focused on delivering impactful solutions. You will have the opportunity to deepen your understanding of business contexts and apply your analytical skills to solve intricate problems. By anticipating client needs and embracing ambiguity, you will contribute to the success of our clients and the firm. This position offers a platform to enhance your personal brand and technical skills while working within our Customer practice.

Responsibilities

Data Science & Analytics Leadership:

Lead the design, development, and governance of data science models for trade promotion optimization, baseline and uplift forecasting, price elasticity, channel/customer segmentation, and anomaly detection on trade spend and volume variances.

Own solution architecture for RGM analytics environments: data model design, 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 stakeholders—CDO, VP Finance, Trade Marketing, Sales Ops—to 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.

What You Must Have

MBA from a premier B-School (Analytics / Strategy / Finance preferred); OR

Master's or Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, or Engineering from a Tier 1 institution with commensurate experience depth.
8–11 years of total experience, with at least 4–5 years in data science, advanced analytics, or quantitative modeling roles in commercial/RGM/TPM contexts. 
Trade Promotions Management: End-to-end TPM lifecycle fluency—Master Data, Funds Management, Volume Planning, Promotion Planning, Optimization, Accruals, Payments, Post Event Analytics, Reporting—with 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 contexts—forecasting, 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.

What Sets You Apart

Data Science & Quantitative Modeling:

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.

Strong model governance capabilities: documentation, version control, sensitivity analysis, performance monitoring, and stakeholder-facing explainability.

Ability to lead technical design reviews and make defensible modeling choices in client-facing settings.

TPM / RGM Domain Expertise:

Demonstrated leadership on RGM analytics engagements for Consumer Goods, Retail, or CPG clients, from scoping through delivery.

Deep familiarity with T/S ratio construction, net revenue waterfall architecture, and trade fund effectiveness frameworks.

Experience advising on target-setting methodology, promotional calendar planning, and post-event reconciliation processes.

Hands-on exposure to at least one TPM/RGM platform (Salesforce Consumer Goods Cloud, SAP TPM, Anaplan, o9) from a data and analytics integration perspective.

Data Engineering & Platforms:

Advanced SQL capability for complex data extraction, transformation, aggregation, and validation across heterogeneous enterprise data sources.

Experience architecting and governing data pipelines from SAP, Salesforce, and other ERP/CRM sources to analytical consumption layers.

Familiarity with cloud data platforms: Databricks, Snowflake, Azure Synapse, BigQuery, or equivalent.

Experience with CI/CD practices for analytical assets; version control (Git); and structured environment promotion (Dev/Test/UAT/Prod).

Analytics Visualization & Insight Communication:

Advanced proficiency in Power BI, Tableau, or equivalent for KPI dashboard design and insight packaging.

Ability to structure and deliver executive-level analytical narratives: from data to insight to commercial recommendation.

Experience building analytical operating models and cadences for client RGM functions (weekly/monthly review decks, exception reports, scenario outputs).

Delivery & Project Leadership:

Proven track record leading analytics workstreams or small teams (3–8 members) in management consulting engagements.

Agile/Scrum delivery experience including sprint planning, backlog management, defect triage, and release governance; tools such as Jira/Azure DevOps.

Strong risk identification, dependency management, and escalation discipline.

Travel Requirements

Up to 40%

Job Posting End Date