Senior Data Operations Analyst - Stat Ops

This position is for Stat Ops team for T&D; business for Gurgaon Location. Have a fair understanding of Operational and Technical expertise processes within GFK & NIQ production for One factory. Responsibilities will include execution of Eastern Europe data acquisition, validation, problem-solving and associated project work and ensure clean data for client insights. This includes understanding and representing the respective local market conditions in the operations processes, as well as executing defined country “onshore” work. This entails engaging local and regional partners like Retail Services, Retailers (clients), Data Science and Output Teams.  

1. Production & Process Management

• Lead end-to-end production workflows, including database project setup, BP/RBBP (split/merge) management, and data order scheduling.
• Execute and coordinate Input Operations and production tasks to ensure on time delivery (OTD) and data trendability; investigate data inquiries with local, regional, and offshore teams.
• Manage rework processes (e.g., back data rework, base channel rearrangement), including impact analysis and alignment with Client Operations (CO retains final decision rights).
• Define, document, and govern operational processes; maintain updated documentation with exception‑tracking mechanisms.
• Provide technical and process expertise to support the deployment of the Consumer Information Platform (CIP) and guide remote teams through effective project execution.
• When applicable, execute complex PG MDQC processes.
2. Quality Assurance & Root Cause Analysis (RCA)

• Support to RCA process and root-cause investigations, including QE analysis and Level 1 methodology-related client query resolution.
• Monitor and analyze Key Quality Indicators (KQIs) and process KPIs; propose and follow through on improvement actions.
• Oversee MDQC management: provide clarifications, perform supervision and validation, and execute required MDQC sign‑off.
• Prepare and maintain accurate KPI tracking dashboards to improve OTD and data accuracy.
• Detect non-standard data patterns and escalate potential issues to Data Science (Dsci) and DOLs.
• Coordinate Data Enrichment improvement initiatives with country teams.
3. Compliance & Data Integrity

• Ensure adherence to industry standards, methodologies, and regulatory requirements while safeguarding data integrity and reliability.
• Oversee shop classification and panel security; ensure completeness and quality of MDM Shop Master data (execution performed by DO Panel Data).
• Manage and test extrapolation processes, including standard compensation, no modeling, and non‑standard compensation; provide guidance to Data Operations on methodology (excluding no-modeling guidance).
• Execute retailer sales modeling processes (e.g., injection, validation) using internal and external sources for standard modeling.
• Analyze PI and regional issues; identify and escalate method- or product-related concerns.
• Address shop creation and modeling issues, including MDQC appearances.
• Resolve Level 1 methodology clarification requests with accuracy and consistency.
4. Automation, Standardization & Continuous Improvement

• Identify automation opportunities across daily operational processes; implement solutions using R, Python, and Excel Macros, and explore ML/AI applications where feasible.
• Drive global/regional initiatives focused on workflow enhancement, automation, and methodological standardization.
• Integrate Data Science recommendations into Data Operations, with special focus on Statistical Operations.
• Improve process efficiency and consistency by standardizing method-related tools, workflows, and documentation.
5. Stakeholder Management & Communication

• Ensure clear, timely, and effective communication with onshore, local, regional, and offshore stakeholders; manage client queries with precision.
• Communicate appropriately during error or incident situations; ensure accurate escalation and downstream updates.
• Collaborate with Retailers, Reference Data, Data Science, Output Teams, and MI Delivery Leads to collect input, coordinate tasks, and improve data quality.
• Operate effectively in a virtual and multicultural environment, ensuring strong cross‑departmental collaboration.
6. Monitoring, Reporting & Analytical Insights

• Develop, maintain, and monitor KPI/KQI dashboards; track exceptions and evaluate performance trends.
• Conduct regular analytical reviews based on KPI results, client feedback, escalations, and MDQC changes.
• Proactively identify unusual data behavior or irregularities and route insights to relevant expert teams for review and resolution.
7. Capability Building & Knowledge Management

• Provide technical mentorship to team members, ensuring proper understanding of system enhancements, MDQC requirements, and methodological standards.
• Maintain up‑to‑date operational and methodological documentation; ensure effective knowledge transfer to onshore, nearshore, and offshore resources.
 Qualifications

• Working experience of proprietary software, Ops Process within NielsenIQ domain 
• Min 2-4 years of experience
• Common business language knowledge (English): speaking and writing with fluency 
• Problem-solving, ability to understand and analyse data 
• Ability to train and to explain technical elements to different stakeholders 
• Ability to monitor activities, a good understanding of KPIs 
• Process-driven - ability to define and refine processes to ensure continual improvement in quality and on-time delivery 
• Proven organizational skills 
• Presentation skills 
• Process improvement methodologies 
• Project management skills - ability to accurately scope project requirements, manage stakeholder expectation 
• Bachelor’s Any Graduate, preference given to Mathematics, Statistics, Economics, Commerce, BBA 
• Master’s degree (Commerce, Statistics, Mathematics or a related field) 
• Exposure to SQL/Python and ML/AI and working with large datasets

Function: General Business
Experience Level: Mid-Senior Level