Product Operations Analyst (L1)

Commerceiq; Bengaluru; On-site; INR 600,000 - 900,000; Full time

Job summary

CommerceIQ is seeking an entry-level Product Operations Analyst to support and scale product data operations for our Digital Shelf Optimization platform. The role emphasizes accuracy, scalable processes, and hands-on operational execution across customer accounts.

You will work with product tagging, PIM matching, catalog maintenance, and automation exploration, learning workflows to identify automation opportunities and contribute to AI-enabled improvements.

Qualifications

• Graduate with at least one internship in operations, data, analytics, or a related hands-on role.
• Strong attention to detail and a genuine bar for getting things right.
• Comfort working with large datasets and structured, repetitive workflows.

Responsibilities

• Execute day-to-day product operations: tagging, catalog maintenance, and configuration updates across customer accounts to defined quality standards and turnaround times.
• Validate product classifications, taxonomy mappings, and catalog configurations to maintain high data quality.
• Follow SOPs consistently and flag unclear or erroneous processes.
• Resolve routine operational issues and prepare context for cross-functional input.
• Identify repetitive, rules-based steps for automation and raise them.

Skills

Attention to detail

Communication

Curiosity

Automation mindset

AI experimentation

Data handling

Education

Bachelor's degree

Tools

SQL

Python

Scripting

Job description

The Company

CommerceIQ is building the AI platform that runs commerce for the world's largest brands. We are not selling AI demos. We are shipping AI agents for content, media, and sales into the workflows of the Fortune 100 every week.

• 2,200+ Customers
• 10 of Top 12 CPG Companies
• 900+ Retailers Connected
• $200M+ Raised

Customers include Coca-Cola, Nestlé, Colgate-Palmolive, Mondelez, Samsung, and Kellogg's. Backed by SoftBank, Insight Partners, and Madrona. Headquartered in Mountain View with teams across the US, India, Canada, and the UK. Pre-IPO.

About the Role

We are looking for an entry level Product Operations Analyst to support and scale product dataoperations for our Digital Shelf Optimization platform. This role is responsible for maintaining the quality, accuracy, and scalability of productoperations across customer accounts. The day-to-day work is hands-on operational execution;product tagging, banner tagging, PIM matching, catalog maintenance and configurationchanges across customer accounts. It demands accuracy, consistency and a high tolerance fordetail. We are actively investing in AI-assisted and automated operations and the analysts wholean into that work are the ones who move up to L2 and beyond.

Key Responsibilities

• Execute day-to-day product operations: product tagging, banner tagging, PIM matching,catalog maintenance, and configuration updates across customer accounts, to definedquality standards and turnaround times.
• Validate product classifications, taxonomy mappings, and catalog configurations tomaintain high data quality.
• Follow operational playbooks and SOPs consistently, and flag cases where the processis unclear, broken, or producing errors.
• Resolve routine operational issues, and consolidate the ones that need cross-functionalinput with enough context to be actioned quickly.
• Learn the workflows well enough to identify repetitive, rules-based steps that arecandidates for automation — and raise them.

Required Qualifications

• Graduate (bachelor's degree), with at least one internship in operations, data, analytics,or a related hands-on role.
• Strong attention to detail and a genuine bar for getting things right rather than just done.
• Comfort working with large datasets and structured, repetitive workflows without losingaccuracy.
• Exposure to SQL, Python, or any scripting, even from coursework or personal projects.
• Clear written and verbal communication.
• Curiosity about how the work could be done faster or automatically and the drive to acton it.
• Hands-on experimentation with generative AI or automation tools.

How success is measured

• Accuracy and throughput on product operations activities.
• SLA adherence on change requests and operational tasks.
• Consistency and reliability of execution against SOPs.
• Automation opportunities surfaced and, over time, contributed to.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any other category prohibited by applicable law.