Analyst

Overview

The Analyst - Forecast Intelligence supports the evolution of Connected Forecasting across Demand, Pricing, Promotion, Network, and Fulfillment, monitoring forecast accuracy and bias and translating data into actionable insights.

What you'll do

• Monitor forecast accuracy and bias across products, locations, channels, and forecast horizons; investigate trends, anomalies, and drivers of performance.
• Build and maintain data pipelines for analytical needs, including extraction, transformation, validation, and scheduled refreshes of forecast, sales, pricing, promotion, inventory, and fulfillment data.
• Develop dashboards, scorecards, and repeatable analyses that connect forecast performance to business outcomes and highlight opportunities for action.
• Perform root-cause analysis to distinguish data quality issues, changing business conditions, and forecasting limitations; recommend improvements with supporting evidence.
• Partner with Product, Data Science, Engineering, and business teams to define success metrics, evaluate forecasting enhancements, and inform prioritization.
• Use AI tools to accelerate data exploration and insight generation, and to write simple, reusable SQL and Python code for complex analytical tasks; validate generated code and findings before use.
• Automate recurring analytical workflows and document data definitions, assumptions, and methodologies to ensure consistent, reliable insights.

What you'll need

• Bachelor's degree in computer science, computer information systems, or related field, or equivalent years of experience in lieu of education requirement, if applicable.
• 2–5 years in analytics or business intelligence; retail or supply chain experience preferred.
• Ability to turn raw data into insights and visualizations using Excel or Power BI.
• Experience investigating datasets with millions of records and identifying root causes.
• Proficiency in complex SQL and ETL.
• Proficiency in Python, including NumPy and pandas.
• Proficiency in GCP or another cloud environment.
• Ability to use AI effectively for analysis and insight generation.
• Strong analytical reasoning, critical thinking, and prioritization.
• Clear written and verbal communication, including management presentations.
• Strong understanding of supply chain and replenishment concepts.

Nice to have

• Master's degree in computer science, CIS, or related field.
• Ability to apply statistical methods to business problems.
• Hands-on experience applying and evaluating analytical models, such as time-series forecasting, regression for price elasticity or promotional lift, anomaly detection, or clustering for product and location segmentation.
• Familiarity with forecast evaluation, including accuracy and bias metrics, backtesting, and comparing performance against baseline models.

Details

• Based at the on-site office in Bengaluru.