Overview
We are looking for an experienced and self-driven Analytics COE senior consultant to independently drive client discussions, analytics presales, solutioning, consulting, and account-mining initiatives.
The individual will partner with sales, account, vertical, and delivery leaders to identify growth opportunities, understand client priorities, shape differentiated analytics and AI propositions, and progress opportunities from discovery through proposal and closure.
This is a hands-on, client-facing role requiring strong analytics consulting experience, executive presence, commercial orientation, and the ability to operate independently. The ideal candidate should have a demonstrated track record of growing an analytics business through new wins, account expansion, and the conversion of analytics opportunities into scalable engagements.
Key Responsibilities
1. Client Advisory and Consulting
- Independently lead discovery sessions, workshops, and solution conversations with senior business, analytics, data, and technology stakeholders.
- Understand the client's business priorities, operating context, analytics maturity, and decision-making challenges.
- Translate ambiguous requirements into clearly defined analytics opportunities, solutions, and transformation roadmaps.
- Bring relevant industry perspectives, benchmarks, leading practices, and analytics and AI use cases into client conversations.
- Develop executive-level POVs, recommendations, and client-ready narratives, while building relationships with existing and new stakeholders.
2. Analytics Presales and Sales Support
- Partner with sales and account teams across the opportunity lifecycle, from qualification and discovery through solutioning, proposal development, presentation, negotiation, and closure.
- Lead responses to RFPs, RFIs, proactive proposals, and strategic analytics pursuits.
- Personally develop solution storylines, proposals, presentations, operating models, roadmaps, effort estimates, and value propositions.
- Lead capability presentations, demos, solution workshops, and senior client meetings as the analytics subject-matter leader.
- Ensure proposed solutions are differentiated, practical, scalable, commercially viable, and linked to measurable business outcomes.
3. Account Mining and Revenue Growth
- Develop analytics growth plans for priority accounts in collaboration with account and delivery leaders.
- Identify whitespace and adjacent opportunities based on current engagements, stakeholder priorities, and the client's business agenda.
- Build relationships with new functions and decision-makers beyond the current scope of engagement.
- Convert client needs and account insights into qualified opportunities, pursuit plans, and actionable next steps.
- Independently drive selected opportunities and contribute directly to analytics pipeline, new wins, account expansion, and revenue growth.
4. Solutioning and Commercial Shaping
- Structure analytics solutions with clearly defined outcomes, workstreams, data requirements, methods, deliverables, governance, and adoption plans.
- Shape integrated solutions spanning business consulting, data engineering, BI, advanced analytics, data science, machine learning, GenAI, and agentic AI.
- Determine the appropriate engagement construct, including assessments, pilots, MVPs, projects, managed services, or phased transformation programs.
- Define delivery models, team structures, estimates, timelines, assumptions, risks, and commercial options.
- Own the core solution and client narrative while involving specialists for specific domain or technical inputs.
- Balance client value with differentiation, delivery feasibility, scalability, risk, and margin considerations.
5. Engagement Oversight and Expansion
- Bring an engagement management perspective to ensure continuity between presales commitments and delivery outcomes.
- Provide consulting oversight during the initial stages of strategic engagements and define success measures, governance, and value tracking.
- Partner with delivery leaders to address risks, refine solution direction, and maintain alignment with client expectations.
- Ensure analytical outputs are embedded into business decisions and workflows rather than delivered as standalone models or dashboards.
- Identify follow-on opportunities arising from ongoing engagements and help convert them into expanded scopes.
6. COE and Capability Development
- Guide COE teams supporting solutioning, consulting, demos, accelerators, and market-facing collateral.
- Develop reusable analytics propositions, solution blueprints, POVs, case studies, demo narratives, and estimation models.
- Prioritize capability development based on market demand, account opportunities, competitive differentiation, and commercial potential.
- Collaborate with domain, data engineering, data science, AI, product, marketing, and delivery teams to develop integrated propositions.
- Coach team members on consulting, solutioning, executive communication, and proposal development.
Qualifications and Experience
Must Have
- Education and experience: Bachelor's or Master's degree in a relevant discipline, with 18 to 22 years of experience in analytics consulting, analytics services, or data-led transformation. An MBA or equivalent qualification would be advantageous.
- Core role experience: Significant experience in analytics solutioning, presales, consulting, and senior client-facing roles, with proven ability to independently lead discovery, solution workshops, executive presentations, and complex pursuits.
- Revenue growth: Demonstrated track record of growing an analytics business through new wins, account mining, cross-sell, expansion, or conversion of pilots into scaled engagements, with evidence of direct contribution to pipeline and revenue growth.
- Solution development: Experience developing analytics solutions from problem definition through solution approach, operating model, effort estimation, value case, and commercial construct.
- Communication: Strong experience preparing executive-quality proposals, presentations, POVs, and recommendations, supported by excellent storytelling and stakeholder-management skills.
- Analytics and technology breadth: Broad understanding of BI, advanced analytics, data science, machine learning, forecasting, experimentation, optimization, and AI-enabled analytics, with sufficient depth to work effectively with technical specialists.
- Commercial acumen: Experience with effort estimation, pricing, deal shaping, managed-service models, and business-case development.
- Independent ownership: Ability to operate independently, manage multiple pursuits, and deliver high-quality work with limited supervision.
- Collaboration: Experience working across sales, account management, domain, solutioning, and delivery teams in a matrixed environment.
- Location: Based in Mumbai and willing to travel for client meetings and workshops as required.
Preferred Experience
- Experience with an analytics consulting firm, analytics services provider, technology services company, or similar client-facing organization.
- Exposure to industries such as retail, consumer products, financial services, communications, technology, or manufacturing.
- Experience developing analytics propositions, accelerators, demos, thought leadership, or go-to-market assets.
- Familiarity with data and analytics platforms such as Databricks, Snowflake, AWS, Azure, GCP, and leading BI platforms.
- Understanding of GenAI and agentic AI applications within analytics and enterprise decision-making, along with experience working with global clients and distributed delivery teams.