Data Insight Analyst [T500-29603]

About Albertsons Companies Inc.:
As a leading food and drug retailer in the United States, Albertsons Companies, Inc. operates over 2,200 stores across 35 states and the District of Columbia. Our well-known banners across the United States, including Albertsons, Safeway, Vons, Jewel-Osco and others, serve more than 36 million U.S customers each week.
We build and shape technology solutions that solve customers’ problems every day, making things easier for them when they shop with us online or in a store. We have made bold, strategic moves to migrate and modernize our core foundational capabilities, positioning ourselves as the first fully cloud-based grocery tech company in the industry.
Our success is built on a one-team approach, driven by the desire to understand and enhance customer experience. By constantly pushing the boundaries of retail, we are transforming shopping into an experience that is easy, efficient, fun and engaging.
About Albertsons Companies India:
At Albertsons Companies India, we're not just pushing the boundaries of technology and retail innovation, we're cultivating a space where ideas flourish and careers thrive. Our workplace in India is a vital extension of the Albertsons Companies Inc. workforce and important to the next phase in the company’s technology journey to support millions of customers’ lives every day.
At the Albertsons Companies India, we are raising the bar to grow across Technology & Engineering, AI, Digital and other company functions, and transform a 165-year-old American retailer. At Albertsons Companies India associates collaborate directly with international teams, enhancing decision-making processes and organizational agility through exciting and pivotal projects. Your work will make history and help millions of lives each day come together around the joys of food and inspire their well-being.
Job Summary:
This role leads complex statistical and analytical initiatives that drive omni-channel growth, loyalty program performance, personalization strategy, and digital marketing optimization. You will apply advanced modeling techniques and experimentation frameworks to shape customer experiences and influence strategic decisions across grocery retail and eCommerce.
Role and Responsibilities:
Advanced Statistical Modeling & ML Support:
Lead sophisticated modeling initiatives, including:
Multivariate and logistic regression for driver analysis
Survival analysis for churn forecasting
Uplift modeling for retention and offer targeting
Marketing attribution and MMM (Marketing Mix Modeling)
Clustering using advanced approaches (mixture models, DBSCAN)
Develop features and oversee model evaluation using statistical rigor (AUC, lift curves, ROC).
Customer & Marketing Science Leadership:
Drive customer lifecycle and behavioral analytics across acquisition, activation, loyalty engagement, and retention.
Lead design and analysis of personalization routines (next-best-action, recommendation ranking, offer targeting).
Conduct promotional and pricing optimization analyses using elasticity modeling and constrained optimization techniques.
Experimentation Strategy & Causal Methods:
Oversee A/B and multivariate experimentation programs using advanced causal inference (CUPED, diff-in-diff, synthetic controls).
Provide experimentation strategy to product managers and marketing leads, ensuring strong statistical governance.
Omnichannel & eCommerce Insights:
Analyze digital shopper journeys across search, product discovery, cart behavior, and fulfillment paths.
Integrate insights from store, digital, loyalty, and marketing channels to provide executive-level recommendations.
Leadership & Influence:
Present insights to senior leadership, influencing eCommerce, merchandising, and loyalty strategy.
Mentor and manage junior/advanced analysts on statistical methods, experimentation design, and storytelling.
Establish best practices and analytical standards across the team.
Required Experience:
Bachelor’s or master’s degree in a quantitative field such as Statistics, Data Science, Applied Mathematics, or Computer Science.
3–6 years of analytics experience with significant exposure to eCommerce, digital marketing, loyalty programs, or omnichannel retail.
Expert SQL skills and significant experience with large datasets in Snowflake, Databricks, or similar platforms.
Strong proficiency in Python (pandas, scikit-learn, stats models) for modeling, feature engineering, and evaluation.
Extensive experience in statistical modeling, time-series forecasting, clustering, and optimization.
Deep familiarity with marketing analytics (attribution modeling, MMM, incrementality, campaign effectiveness).
Proven ability to present complex statistical results to executives and guide strategic decisions.

Work arrangement
No