Arun Solay

Senior Business Analyst at Flipkart with 2+ years converting large-scale e-commerce data into revenue impact.

Built

Flipkart's first AI/LLM analytics infrastructure using LangChain and Python, eliminating 60%+ of manual analytical workflows.

Core skills: SQL, Python, A/B Testing, Machine Learning, and cross-functional execution at scale.

Senior Business Analyst at Flipkart (2026-09 – Present)

• Built Flipkart's first LLM-powered analytics infrastructure using LangChain and Python: multi-step RCA agents that autonomously query data, identify anomaly root causes, and surface findings without human intervention, eliminating 60%+ of manual analyses and reclaiming ∼8 hrs/week per analyst across multiple business verticals.

Business Analyst at Flipkart (2024-07 – 2026-08)

• Drove INR 15M in incremental annual revenue by building Flipkart's first ML-powered cross-sell targeting engine: a gradient-boosted model on diaper purchase signals that lifted personalization precision by 30% across toys, apparel, and books.
• Eliminated pricing blind spots across 60K+ SKUs by engineering an automated real-time competitive monitoring system; compressed pricing decision cycles from days to hours, enabling proactive margin recovery across high-velocity categories.
• Improved peak-season fulfillment SLA compliance by 8% by leading cross-functional RCA spanning 10+ verticals and 20+ regions; surfaced last-mile bottlenecks and co-designed targeted ops interventions deployed at scale.
• Reduced product return rate by 10% in under 60 days by conducting a Python/SQL deep-dive across 100K+ orders; uncovered root-cause patterns across high-return sellers and defective SKUs, triggering targeted deactivations, structured retraining programs, and catalog corrections that scaled across categories.

Product and Growth Intern at Bytical (2024-04 – 2024-06)

• Mapped the competitive landscape across 10+ industry players, surfacing 5+ feature gaps and 3 differentiation opportunities; synthesized findings into a leadership-facing business case that shaped the next-quarter product roadmap and repositioning strategy.
• Owned the revenue lifecycle for 10+ enterprise accounts: from pitching and negotiation to onboarding and post-deployment support; standardized onboarding playbooks and drove measurable NPS improvement and retention uplift.

Machine Learning Intern at Larsen and Toubro (2023-05 – 2023-07)

• Reduced manual building simulation time by 80% by developing XGBoost-powered Python dashboards with interactive data visualization, automating Useful Daylight Illuminance (UDI) forecasting for energy-efficient design.
• Contributed to a projected 10% reduction in annual energy consumption by integrating machine learning model outputs into architectural plans for LEED-certified green construction projects.

B.Tech in Electrical and Electronics Engineering – National Institute of Technology, Karnataka (2020-09 – 2024-04)