Master Marketplace Analytics & Drive Buy Box Competitiveness for Top US Brands

Are you an analytical data specialist who understands the hidden algorithms behind digital storefronts? Zorba AI is seeking a highly precise Data Analyst (E-commerce Buy Box) with 2–5 years of experience to join our core intelligence team in Chennai.

In the high-stakes world of online marketplaces, winning or losing the Buy Box dictates millions of dollars in transaction volumes. In this role, you will act as the master of marketplace metrics for a leading US-based client. You will leverage an elite technical stack across SQL, Python, and Tableau to parse high-velocity transaction telemetry, build predictive pricing models, run regression testing, and uncover exactly why a brand loses the checkout button—turning raw metrics into a strategic competitive advantage.

The Role: Data Analyst (E-commerce Buy Box)

As an E-commerce Data Specialist, you will sit at the intersection of business intelligence, data engineering, and pricing strategy, working in an agile environment aligned with US market timelines.

[Marketplace Feed Data] ──> [SQL Extraction & Python Pipeline]
                                           │
                                           ▼
[Buy Box Win Optimization] <── [Tableau Dashboards & KPIs]

Key Responsibilities:

• Tableau Dashboard Engineering: Design, develop, and govern interactive corporate dashboards tracking mission-critical metrics including Buy Box win rate, seller ratings, pricing elasticity, conversion velocity, and real-time inventory health. Masterfully deploy calculated fields, parameters, Level of Detail (LOD) expressions, and blended data models.

• Advanced SQL Extraction: Author highly optimized, complex SQL queries utilizing multi-tier joins, Common Table Expressions (CTEs), subqueries, and advanced window functions to aggregate data out of immense relational cloud data lakes.

• Python Automation & EDA: Architect automated reporting pipelines and perform rigorous Exploratory Data Analysis (EDA) using Pandas and NumPy. Leverage Scikit-learn to conduct regression testing on pricing, inventory thresholds, and fulfillment models.

• Buy Box Diagnostics: Map and dissect buy box eligibility variables (e.g., automated repricing, fulfillment methods like FBA/FBM, seller defect rates). Trace the technical root causes behind Buy Box suppression and loss.

• Portfolio Matrix Tracking: Oversee macro and micro ecommerce performance metrics, tracking Advertising Cost of Sales (ACOS), Return on Ad Spend (ROAS), Total ACOS (TACOS), Best Sellers Rank (BSR), and buy box capture percentages.

Technical Prerequisites & Required Skills

We are looking for a data storyteller who thrives in fast-paced retail environments and possesses an deep technical curiosity for marketplace logic.

Required Qualifications:

• Experience: 2–5 years of professional experience in Data Analytics, Business Intelligence, or Marketplace Analytics roles—ideally supporting US-based clients.

• Education: Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or an equivalent quantitative discipline.

• SQL Mastery: Deep understanding of relational databases, data cleansing, and query tuning for performance optimization.

• Python Ecosystem: Practical competency writing clean scripts using Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn.

• BI Infrastructure: Strong advanced production experience deploying enterprise reports on Tableau Desktop and Server.

• Marketplace Familiarity: Clear understanding of Amazon Buy Box mechanics, seller tier impacts, and e-retail metrics.

Preferred Skills & Infrastructure Exposure (Bonus Points):

• Cloud Architecture: Hands-on familiarity with cloud data store ecosystems such as AWS (Redshift, S3, Glue, Athena) or Google Cloud Platform (BigQuery).

• CI/CD & Code Governance: Experience tracking production script versions via Git.

• Advanced Analytics: Direct exposure to marketplace data feeds, catalog analytics, A/B testing methodologies, competitive benchmarking, or automated price optimization models.

• Operational Agility: Prior experience navigating fast-paced BPO/KPO frameworks and comfort operating within US time zone / PST shift structures.

What Zorba AI Offers

• High-Impact Portfolio: Direct exposure managing technical data pipelines for high-volume, leading consumer brands in the United States.

• Advanced Tech Stack: A culture that encourages moving beyond basic spreadsheets into cloud data warehousing, automated python pipelines, and statistical modeling.

• Collaborative Growth: Fast-paced, agile sprint cycles with continuous technical mentorship and stakeholder exposure.