#ACN I&P - GN - SONG - AI & Data - Commerce - Decision Science -  Consultant

Management Level: - Ind & Func AI Decision Science Consultant – Level 9
Location: Gurgaon / Bangalore / Mumbai / Hyderabad

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, RAG pipelines, vector databases/retrieval, LLM APIs, prompt engineering, agent/tool integration, evaluation and guardrails, Power Platform (BI + App), Tableau and Custom Frontend

Soft skill: Client Management, Verbal and written communication, Team collaboration skills, e-mail writing, PowerPoint and Excel reporting, pro-active initialization, accountability

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, and integration of agentic workflows with commerce, CRM, marketing and campaign platforms.

Job Summary

As part of our Data & AI practice supporting SONG Commerce, you will combine hands-on analytics, AI/ML and Agentic AI engineering with client problem solving. You will translate commerce challenges into scalable analytical and agentic solutions spanning pricing, promotions, assortment, personalization, recommendations, next-best action and related customer or commercial decisions.

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
  • Hands-on knowledge of NLP, Large Language Models, LangChain/LangGraph and RAG; design retrieval, tool-calling and agentic workflows with appropriate grounding, guardrails and evaluation for commerce use cases.
• Manage client relationships and expectations and communicate insights and recommendations effectively.
• Contribute to capability building and reusable assets for AI-enabled and Agentic Commerce.
• 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
• Advise clients on data-driven commerce decisions and translate analytical / agentic outputs into practical pricing, promotion, assortment, personalization and customer-action recommendations.

Professional & Technical Skills:

Must have at least 4+ years of work experience in Marketing analytics with a reputed organization.

3+ 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
• Knowledge of CPG, Retail industry.
• Proficient in Excel, MS word, PowerPoint, etc.
• Strong client communication.

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