Key Responsibilities
1. Business Requirements & Solution Design
- Lead end-to-end business requirements gathering, stakeholder workshops, and discovery sessions
- Translate complex retail business challenges into clear, structured, and prioritized requirements
- Design cutting-edge AI/ML and data-driven solutions across retail functions such as merchandising, Ecommerce, supply chain, marketing, store ops, pricing etc
- Develop user journeys, process flows, data flows, and functional specifications
- Partner with data architects, data engineers, and data scientists to shape scalable and feasible solutions
2. Data Analysis & Data Quality Assessment
- Analyze large and complex retail datasets to uncover trends, patterns, and anomalies. Identify data quality issues, root causes, and potential business impacts
3. AI/ML Use Case Identification & Value Realization
- Identify and evaluate high-impact AI/ML opportunities across retail (e.g., demand forecasting, recommendation engines, markdown optimization, inventory optimization, churn prediction)
- Create business case assessments by diagnosing process inefficiencies using data insights and operational assessments and recommend improvements by leveraging automation, AI, predictive analytics, and data-driven workflow
- Partner with data science teams to translate business needs into ML problem statements and success metrics
5. Pre-Sales & Proposal Development
- Lead creation of client proposals, solution decks, RFP responses, and use case catalogs
- Support sales teams with solutioning, effort estimation, and value proposition development
6. Cross-Functional Collaboration
- Collaborate closely with technical teams, retail business stakeholders, PMO, UX designers, and leadership
- Ensure alignment throughout the project lifecycle—from ideation to deployment
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Required Skills & Experience
Technical & Analytical
- Strong proficiency in data analysis tools (Excel, SQL, Python basics preferred)
- Exposure to AI/ML concepts, model lifecycle, and data science workflows and ability to interpret ML outputs, KPIs, and performance metrics
- Knowledge of cloud platforms (Azure, AWS, GCP) is a plus
Retail Domain Expertise
- Deep understanding of end-to-end retail operations, including: Merchandising & Assortment Planning, Inventory & Supply Chain, Pricing & Promotions, Store Operations , Ecommerce, Customer Analytics & Omnichannel Journey
Business & Consulting
- Exceptional requirements elicitation, documentation, and stakeholder management skills
- Experience in designing data-driven and AI-enabled retail solutions
- Strong presentation and storytelling skills for executive audiences
- Ability to create proposal content, value narratives, and solution overviews
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Qualification
- Bachelor's or Master's degree in Business, Data/Analytics, Engineering, or related field
- 8–12+ years of experience in Retail Consulting, Business Analysis, or Digital Transformation
- Proven experience in AI/ML-led transformation programs is highly desirable
- Experience with mid to large Retailers in Europe or U
Preferred Attribute
- Strategic thinker with the ability to simplify complex concepts
- Curious, innovative mindset with passion for using data & AI to transform businesses
- Ability to work in fast-paced environments and manage multiple initiatives simultaneously
- Excellent communication skills with ability to engage with business stakeholders and internal team
Skill
- Business Acumen Response
- Communication Influencing & Negotiation Skill Design
- Thinking Solutioning Expertise Proactive
- Approach Domain expertise Independent Learning
- Good communication skill
