PlanSmart - Senior AI Success Consultant

Impact Analytics; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Impact Analytics in Bengaluru is looking for an AI Success Senior Consultant to provide post-go-live support for Merchandise Planning solutions. This role involves owning functional issue resolution and mentoring junior consultants.

The ideal candidate will have 5-8 years of experience in post-go-live support for supply chain SaaS solutions, with expertise in configuring planning engines and resolving functional tickets. Strong customer communication skills and a mentorship mindset are essential.

Qualifications

• 5-8 years of experience in post-go-live support for supply chain SaaS.
• Track record of resolving over 500 functional tickets with >95% CSAT.
• Customer-first communicator who thrives in high-volume environments.

Responsibilities

• Own functional tickets and ensure data accuracy.
• Diagnose and resolve post-go-live defects in Merchandise Planning.
• Mentor Customer Success Consultants on best practices.

Skills

Post-go-live support

Merchandise Financial Planning

Configuring planning engines

Customer communication

Mentoring

Basic scripting skills

Education

Certification in APICS CSCP, o9, Kinaxis, or Blue Yonder

Tools

SQL

MDX

Python

R

Job description

About Impact Analytics

Impact Analytics™ (Series D Funded) delivers AI‑native SaaS solutions and consulting services that help companies maximize profitability and customer satisfaction through deeper data insights and predictive analytics. With a fully integrated, end‑to‑end platform for planning, forecasting, merchandising, pricing, and promotions, we empower companies to make smarter decisions based on real‑time insights. Powered by over one million machine learning models, Impact Analytics has been leading AI innovation for a decade across retail, grocery, manufacturing, and CPG sectors. In 2025, we are at the forefront of the Agentic AI revolution, delivering autonomous solutions that enable businesses to adapt in real time, optimize operations, and drive profitability.

Role: AI Success Senior Consultant

Our AI Success Senior Consultant is responsible for post‑go‑live support for Merchandise Planning solutions. The role owns functional issue resolution, change request delivery, ticket triage & SLA adherence, and mentorship of junior consultants.

What This Role Entails

• 5-8 years of experience in post‑go‑live support / functional consulting for supply chain SaaS (Blue Yonder, o9, Kinaxis, Anaplan, SAP IBP, etc.)
• Hands‑on expertise in Merchandise Financial Planning and Budget Planning solutions
• Proven ability to configure and debug planning engines (SQL, MDX, data pipelines, simulation)
• Track record of resolving 500+ functional tickets with >95% CSAT
• Experience leading change requests end‑to‑end (Scope → Config → UAT → Deploy)
• Exposure to Agentic AI / autonomous planning agents (o9, Kinaxis, Blue Yonder, etc.)
• Certification in APICS CSCP, o9, Kinaxis, Blue Yonder planning products
• Basic scripting skills (Python, R) for ad‑hoc analytics
• Customer‑first communicator – clear, concise, proactive
• Mentorship mindset – patient teacher, process evangelist
• Thrives in high‑volume, high‑visibility support environments

Functional Ownership & Issue Resolution

• Owner of functional tickets (configuration, workflow, data accuracy)
• Diagnose and resolve post‑go‑live defects in Merchandise Planning modules within SLA
• Validate end‑to‑end workflows for Merchandise Planning solutions

Customer Communication & SLA Management

• Provide daily/weekly ticket updates to customer planners and IT teams
• Host functional deep‑dive sessions during QBR preparation (root cause, resolution path, prevention)
• Maintain SLAs for system availability and incidents

Team Leadership & Knowledge Transfer

• Mentor Customer Success Consultants on best practices, debugging, and AI‑agent tuning
• Build and maintain a knowledge repository (KB articles, runbooks, regression test packs)
• Drive internal process improvements based on recurring ticket patterns