• Contributed to Generative AI projects using LangChain, prompt engineering, and Retrieval-Augmented Generation (RAG) to improve chatbot response accuracy and contextual relevance.

• Designed and tested RAG workflows and prompt strategies to enhance information retrieval and response quality.

• Validated and tested AWS API endpoints using Postman to ensure reliable integration and system performance.

• Supported development of a data-driven volunteer matching system by contributing to AI workflow testing and requirements analysis.

I collaborated cross-functionally with product, BI, and marketing teams in an agile environment to translate complex business requirements into actionable data solutions, driving advanced customer segmentation and behavioral analysis for cross-border SMBs. I facilitated stakeholder workshops and requirements-gathering sessions to map processes, uncover pain points, and prioritize analytics initiatives that aligned with strategic goals, enhancing customer acquisition. Leveraging AWS Athena, I designed and executed optimized SQL queries with CTEs and window functions to process over 85% of historical transaction data across structured and semi-structured formats, enabling data-driven strategic decisions. I conducted RFM and cohort analyses to pinpoint key customer segments, discovering that 62% of SMBs were concentrated in four high-value clusters, directly informing retention and growth strategies. Using Python (NumPy, Pandas, SciPy), I performed data preparation, cleaning, and time-series analysis with Z-score-based outlier detection to identify seasonal trends, improving forecasting accuracy. I implemented robust data validation frameworks with AWS Glue and DataBrew, introducing automated quality checks that ensured 98%+ data integrity and strengthened trust in key business metrics. Additionally, I developed and maintained interactive Power BI dashboards with advanced DAX measures, KPI cards, drill-through filters, and dynamic slicers, enabling real-time segment-level revenue tracking and boosting targeted marketing efficiency by 37%. My work culminated in presenting analytical findings and actionable recommendations to senior stakeholders, which informed strategic decisions, optimized customer acquisition and retention, and drove measurable improvements in overall business performance.

• Analyzed competitor landscape and market trends to identify opportunities and support data-driven business strategies.

• Evaluated company operations and translated analytical findings into actionable insights aligned with client needs.

• Assessed existing dashboards and recommended improvements to enhance data visualization and decision-making.

Partnered with Sales, Marketing, and BI teams in agile environments to gather detailed requirements, conduct stakeholder interviews, and uncover regional market insights, enabling actionable strategies for market expansion across India. Streamlined data integration and ETL workflows using Azure Data Factory and Azure Databricks, improving processing efficiency by 30% and ensuring reliable, high-quality data from SAP, Salesforce, and CRM ERP systems. Directed stakeholder analysis and facilitated JAD sessions to validate business requirements, creating use cases, process flows (Visio), and requirement traceability matrices to align with business goals.

Performed advanced time-series and cohort analyses in Python (Pandas, NumPy) to identify sales growth trends and purchasing patterns, driving targeted marketing that increased revenue by 15%. Applied R for hierarchical clustering and customer segmentation, enabling personalized campaigns that boosted engagement by 20%. Developed optimized SQL queries on Azure SQL Database to transform complex datasets, supporting timely and accurate sales performance reporting.

Led data quality assurance using Azure Data Factory and Databricks, implementing validation rules that reduced errors by 25%. Designed interactive Tableau dashboards with dynamic filters, calculated fields, and LOD expressions, providing granular visibility into regional sales performance and helping increase market share by 10%. Conducted business process mapping and workflow analysis to identify inefficiencies in sales data management, enabling more agile, data-driven decision-making.

• Automated financial and CRM data reports using Excel, enabling efficient identification of discrepancies. This improved reporting accuracy,

streamlined operations, and provided insights to support targeted cross-selling plans and business planning initiatives.

• Conducted in-depth analysis of financial data to optimize reporting workflows. Enhanced reporting efficiency and facilitated better decision-making

by delivering actionable insights, helping the team align with strategic goals and improve client engagement.

• Managed daily client communications and reporting processes, reducing issue escalations by 20%. Ensured timely delivery of accurate reports,

which contributed to increased customer satisfaction and supported stronger client relationship management.

• Reinforced collaboration between departments by providing precise data reports and timely updates. Played a key role in enhancing overall data

accuracy, leading to improved operational efficiency and support for informed, data-driven business decisions.