Mar 2025 – Apr 2026 · 1 yr 1 mo · On-site

• Delivered end-to-end Commercial and Customer Analytics solutions using PySpark and Microsoft Fabric, transforming large-scale transactional and marketing data into actionable insights supporting brand strategy, go-to-market planning, and customer centricity initiatives.
• Designed and implemented statistical and machine learning models (regression, classification, unsupervised learning) using LightGBM, XGBoost, and K-Means clustering to support business decision-making, customer response prediction, and targeting optimization.
• Built advanced customer segmentation frameworks using RFM analysis, z-score binning, clustering, and persona/tier mapping, enabling data-driven audience selection and measurable improvement in commercial outcomes.
• Applied strong statistical rigor including model assumption validation, bias-variance trade-offs, feature relevance assessment, and class imbalance handling (SMOTE, weighted learning) to ensure robust, interpretable, and business-ready analytics.
• Integrated Generative AI and Agentic AI concepts into analytics workflows by:
• Using LLM-powered insight summarization to translate analytical outputs into business-friendly narratives
• Prototyping agent-based analytical assistants to support ad-hoc analysis, insight exploration, and stakeholder Q&A
• Leveraging prompt engineering and structured outputs to standardize insight generation for commercial users
• Worked with HuggingFace models and embeddings to experiment with:
• Customer and transaction representation learning
• Semantic similarity and clustering use cases
• Text and unstructured data enrichment to complement structured analytics
• Demonstrated foundational understanding of deep learning, MLOps concepts, and containerization, enabling effective collaboration with data engineering and platform teams (implementation not limited to core analytics scope).

Apr 2022 – Mar 2025 · 2 yrs 11 mos · On-site

Dec 2019 – Apr 2022 · 2 yrs 4 mos · Pune, Maharashtra, India · On-site

• Conducted secondary research and developed data models to extract insights from data in the specialty chemicals domain.
• Managed a team of 4 consultants and successfully delivered consulting projects and white papers on time.
• Implemented pricing strategies for clients' product lines in the chemical and materials domain.

Jun 2019 – Nov 2019 · 5 mos · Noida, Uttar Pradesh, India · On-site

• Developed pricing strategy for Speciality and Bulk chemicals, creating a dashboard for multiple clients.
• Collaborated on Chemicals and Materials Consulting Projects, analyzing market trends and competitor data.
• Achieved cost savings of 15% for clients through strategic pricing recommendations and market insights.