I&P - GN - SONG - AI & Data - Commerce - Decision Science - Manager

Accenture PLC; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Accenture is seeking an Ind & Func AI Decision Science Manager to lead data, analytics and Agentic AI solutions for commerce clients across pricing, promotion, assortment, personalization and next-best-action use cases. You will guide teams and senior client stakeholders, aligning commercial priorities with scalable solution architecture and delivery.

Role requires 8+ years in data-driven analytics for CGS/retail, strong Azure ML, SQL, Python and LangChain/LangGraph expertise, and a track record

Qualifications

• 5+ years of experience in Commerce / Data Driven Merchandising / Commercial Analytics involving Pricing, Promotions, Assortment Optimization, personalization/recommendations, Route-to-Market or related Retail / CPG capabilities.
• Expertise in Azure ML, SQL, R, Python and PySpark; working experience with LLM application frameworks such as LangChain/LangGraph, RAG and vector retrieval.
• Hands-on with tools like Excel, Word, PowerPoint for communication and documentation

Responsibilities

• Work through project phases from data discovery and commerce problem definition through model/agent build, validation, integration, deployment and handover.
• Define data requirements for SONG Commerce analytics and Agentic Commerce capability.
• Clean, aggregate, analyze, interpret data, and carry out data quality analysis.
• Apply market sizing, lift estimation and experimentation/measurement approaches to pricing, promotions, campaigns, personalization and other commerce decisions.
• Apply non-linear optimization techniques to pricing, promotion, assortment, offer and resource-allocation use cases.
• Use time-series, clustering, causal and descriptive analytics to support merchandising and commerce intelligence, including demand, pricing, promotion, assortment and customer/product decisioning.
• Hands on experience in state space modeling and mixed effect regression.
• Develop and validate AI/ML models in Azure ML and integrate model outputs into commerce decisioning and agentic workflows.

Education

Bachelor/Master’s degree in Statistics/Economics/ Mathematics/ Computer Science or related disciplines

Job description

Management Level: Ind & Func AI Decision Science Manager – Level 7

Location: Gurgaon / Bangalore / Mumbai

Functional: SONG Commerce / Commercial Analytics - pricing, promotion, assortment, personalization, recommendation and next-best-action, route-to-market and revenue growth management; descriptive, diagnostic, predictive and prescriptive analytics

Analytics Models knowledge: Econometric Modeling, Statistical Timeseries Models, Store Clustering Algorithms, Causal Models, State Space Modeling, Mixed Effect Regression, NLP Techniques, Large Language Models, non-parametric models, AI/ML model development, Supervised and Unsupervised Learning, Generative AI and Agentic AI patterns including RAG, agent orchestration, tool calling and multi-agent workflows.

Technical: Azure ML Tech Stack, SQL, PySpark, Python, Cloud Platforms (Azure, GCP), Data Architecture, Data Modeling & Pipelines, LangChain, LangGraph, enterprise RAG, vector retrieval, LLM APIs, agent/tool orchestration, evaluation, guardrails and Agentic AI deployment patterns, Power Platform (BI + App), Tableau and Custom Frontend

Soft skill: Client stakeholders Management, Team leading skills, Team mentoring & Coaching, PowerPoint and Excel reporting, pro-active initialization, accountability, RFPs Solutioning skills, SP-51 Documentation, Delivery management, Project management tool – JIRA, Azure DevOps etc.

Industry Knowledge: Commerce, CPG, FMCG, Retail; understanding of customer, product, pricing, promotion, assortment, campaign and transaction data

Good to have skills:

• AWS Cloud Capability
• Scalable Machine Learning Architecture Design Patterns
• AI Capability Building
• React / Angular frontend development
• DevOps pipelines
• conversational AI
• agent observability/evaluation
• model and prompt governance
• integration of agentic workflows with commerce, CRM, marketing and campaign platforms, D&A Solution Architecture and reusable Agentic Commerce accelerator design

Job Summary As part of our Data & AI practice supporting SONG Commerce, you will lead the shaping and delivery of data, analytics, AI/ML and Agentic AI solutions for commerce clients. You will connect commercial priorities with scalable solution architecture and delivery across pricing, promotion, assortment, personalization, recommendation, campaign activation and next-best-action use cases, while guiding teams and senior client stakeholders.

Roles & Responsibilities

• Work through project phases from data discovery and commerce problem definition through model/agent build, validation, integration, deployment and handover.
• Define data requirements for SONG Commerce analytics and Agentic Commerce capability.
• Clean, aggregate, analyze, interpret data, and carry out data quality analysis.
• Apply market sizing, lift estimation and experimentation/measurement approaches to pricing, promotions, campaigns, personalization and other commerce decisions.
• Apply non-linear optimization techniques to pricing, promotion, assortment, offer and resource-allocation use cases.
• Use time-series, clustering, causal and descriptive analytics to support merchandising and commerce intelligence, including demand, pricing, promotion, assortment and customer/product decisioning.
• Hands on experience in state space modeling and mixed effect regression.
• Develop and validate AI/ML models in Azure ML and integrate model outputs into commerce decisioning and agentic workflows.
• Develop and Manage data pipelines.
• Aware of common design patterns for scalable machine learning architectures, as well as tools for deploying and maintaining machine learning models in production.
• Knowledge of cloud platforms and usage for pipelining and deploying and scaling elasticity models.
• Working knowledge of resource optimization
• Working knowledge of NLP, Large Language Models, LangChain/LangGraph, RAG and multi-agent patterns; guide architecture choices, enterprise integration, guardrails and evaluation for Agentic Commerce solutions.
• Manage senior client relationships and expectations; communicate commerce insights, Agentic AI solution choices, value implications, risks and recommendations effectively.
• Drive capability building and thought leadership in AI-enabled and Agentic Commerce, including reusable patterns, accelerators and propositions.
• Logical Thinking – Able to think analytically, use a systematic and logical approach to analyze data, problems, and situations.
• Notices discrepancies and inconsistencies in information and materials.
• Task Management – Advanced level of task management knowledge and experience. Should be able to plan own tasks, discuss and work on priorities, track, and report progress.
• Client Relationship Development Manage client expectations and develop trusted relationships Maintain strong communication with key stakeholders Act as a strategic advisor to clients on data-driven and AI-enabled commerce decisions across pricing, promotion, assortment, personalization, recommendation and customer activation.

Professional & Technical Skills

5+ years of experience in Commerce / Data Driven Merchandising / Commercial Analytics involving Pricing, Promotions, Assortment Optimization, personalization/recommendations, Route-to-Market or related Retail / CPG capabilities. Strong understanding of econometric/statistical modeling: regression analysis, hypothesis testing, multivariate analysis, time series, optimization; ability to apply these techniques to commerce use cases such as pricing, promotions, assortment, demand and targeting. Expertise in Azure ML, SQL, R, Python and PySpark; working experience with LLM application frameworks such as LangChain/LangGraph, RAG and vector retrieval. Proficiency in non-linear optimization and resource optimization Familiarity with design patterns for deploying and maintaining ML models in production Strong command over commerce, marketing, customer, product, pricing, promotion and transaction data, and the corresponding business processes in Retail and CPG Hands-on with tools like Excel, Word, PowerPoint for communication and documentation

Additional Information

• Bachelor/Master’s degree in Statistics/Economics/ Mathematics/ Computer Science or related disciplines with an excellent academic record undefined undefined undefined
• Experience: Minimum 8+ years of relevant Marketing Analytics experience, with at least 5+ years in end to end Data driven consulting for CGS or Retail Clients
• Educational Qualification: Bachelor/Master’s degree in Statistics/Economics/Mathematics/Computer Science or related disciplines.
• Preferred advanced degrees include M.Tech, M.Phil/Ph.D in Statistics/Econometrics or related field from reputed institutions.

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities. Visit us at www.accenture.com

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