Aishwarya Dhalagade

• Managed business intelligence reporting for Inspira global group, focusing on sales performance,
inventory optimization, customer segmentation, and market trends to drive business growth.
• Extracted, cleaned, and analyzed large-scale datasets using Python and SQL, improving revenue
forecasting accuracy by 30% through predictive modeling.
• Automated ETL pipelines using Python, SQL, streamlining data ingestion, transformation, and
model deployment, reducing manual effort by 50%.
• Developed real-time Power BI dashboards by collaborating with cross-functional teams to
translate business requirements into actionable insights, driving faster decisions and improved
performance across sales, marketing, and operations.
• Leveraged Google Cloud Platform (GCP) for scalable data storage and BigQuery for fast analytical
querying, enabling efficient handling of high-volume datasets and real-time reporting
• Utilized AWS services such as S3 for data storage and Lambda for event-driven ETL workflows,
improving pipeline scalability, reliability, and reducing infrastructure overhead.
• Applied advanced analytics, statistical modeling, and AI-driven insights to uncover key business
trends, optimizing customer engagement and revenue growth.

• Developed integrated retail, sales, and marketing intelligence dashboards using Power BI,
Python, and GCP, enabling decision-making through consolidated campaign performance,
market insights, and ROI analysis.
• Conducted digital, social media, and website audit analyses using Python, LLM-powered insights,
and GenAI reporting to optimize MMM and MTA models.
• Built advanced end to end machine learning models (classification, regression, clustering) for
customer segmentation, churn prediction and sales forecasting, achieving a 20% improvement in
prediction accuracy (MLOps, GCP Vertex AI).
• Executed AI-powered projects (topic modelling, reviews and comments classification, sentiment
analysis) using LLMs (BERT, T5, Gemini AI), Hugging Face, and NLP.
• Designed and implemented marketing analytics strategies to enhance customer engagement
and retention (15% increase), leveraging MMM insights.
• Developed an NLP-based Q&A tool (Gemini AI 1.5 API) integrated within a real-time working
dashboard with context-aware querying, reducing analysis time by 60% (LLMs, RAG).
• Applied digital, social media, and retail campaign analytics to generate actionable insights,
optimizing campaign KPIs and MTA-based attribution (40% increase in conversion rates).
• Automated comment analysis on Meta using BART-large-CNN, sentiment models, and Gemini AI
for reply generation. Achieved 92% sentiment accuracy and reduced manual effort by 70% via
NLP-driven dashboard integration.

• Performed EDA, segmentation, and feature selection on transactions dataset, building a
predictive model with R² = 0.91.
• Visualized key transaction trends to support data-driven decisions in financial analysis.

• Built a Breast Cancer Detection model using Python, achieving 89% accuracy through feature
engineering and hyper-parameter tuning.
• Applied classification algorithms to optimize diagnostic model performance.

• Designed BI dashboards, customer segmentation models, improving targeting precision by 15%.
• Conducted data quality assessments ensuring 95% accuracy for marketing insights.

• Contributed to 3+ collaborative data projects and organized seminars as Campus Datapreneur.
• Promoted a data-driven culture through knowledge sharing and insights delivery.

• Delivered 5 ML projects applying regression, classification, clustering with up to 89% accuracy.
• Used EDA and tree-based models to solve complex business problems with clear
recommendations.