Senior Business Analyst

Roles and Responsibilities:

Job Description for a Senior Retail Business Analyst – Data & AI/ML

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 workflows
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.

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 Journeys

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.

Qualifications

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 US

Preferred Attributes

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 teams

Skills

Business Acumen Response
Communication Influencing & Negotiation Skill Design
Thinking Solutioning Expertise Proactive
approach Domain expertise Independent Learning
Good communication skill