Inquisitive Data Scientist with 8+ years of experience, all through data pre processing with EDA, feature selection, feature
engineering, ML model development, governance. Dashboarding, reporting, statistical analysis, …
Inquisitive Data Scientist with 8+ years of experience, all through data pre processing with EDA, feature selection, feature
engineering, ML model development, governance. Dashboarding, reporting, statistical analysis, working with cross functional
teams in every step to create maximum business impact. Experienced in Insurance, Supply chain, E-Commerce & Content
Analytics domains. Applied LLMs and GenAI for personalized scripting, product messaging and intelligent automation.
Expertise in recommendation systems, predictive risk, customer behavior analytics, cross-sell with next best offer,
renewals and upsell models for insurance. Proven ability to contribute individually and lead teams for almost 4 years, managing
projects from start to finish.
Built an XGBoost model for health insurance upselling, integrating health and bureau data, propensity scores, and sum insured recommendations.
Improved ROC-AUC by 20% and precision/recall by 18%.
Used GenAI to create personalized pitch scripts, boosting sales by 15% through tailored offers to low-risk customers.
Created end to end monitoring pipeline for the same.
Developed predictive ML models using XGBoost, PyTorch, and Keras to forecast customer propensity and recommend the next best product.
Integrated clustering techniques to create customer segments and deliver personalized plan variant suggestions, driving a 3.5% increase in cross-sell policy conversions.
Incorporated bureau data to tailor sum insured recommendations based on creditworthiness and risk profiles.
Leveraged Gen AI & LLMs (GPT-4, fine-tuned models) for personalized product scripting, automated recommendation explanations & FAQ-style responses for customer interactions.
Deployed models through REST APIs for real-time integration with customer engagement platforms.
Built XGBoost models for health insurance upselling, predictive ML models for cross-selling, personalized scripting with GenAI & LLMs, monitoring pipelines.
Conducted cross-platform analysis and customer behavior research, identifying app acquisition touch points using clickstream data to predict cart abandonment likelihood and timing, enabling timely interventions that increased conversion.
Designed and implemented a data pipeline for APP table development using clickstream data, computing key customer journey metrics, leading to improvement in user engagement.
Built analytical dashboards, identified web analytics KPIs, and performed UAT, improving decision-making processes and operational efficiency.
Developed an intelligent dashboard finder tool leveraging NLP techniques to automatically identify and recommend relevant dashboards based on user queries, enhancing accessibility.
Integrated the tool within existing BI platforms to streamline user experience.
Analyzed e-commerce chatbot conversations to identify key KPIs (handover rate, resolution time, sentiment).
Built an NLP-based classification model to predict escalation to human agents using session-level features like intent, delay, and sentiment.
Insights led to workflow redesigns, improving bot resolution rate by 12%.
Conducted customer behavior analytics, designed data pipelines, built analytical dashboards, developed an intelligent dashboard finder tool, analyzed e-commerce chatbot conversations.
Conducted marketing and sales analysis using centroid clustering and cosine distance metrics to identify optimal warehouse locations based on demand and supply patterns, pricing factors, and existing XPO locations for key clients, resulting in a 17% increase in market penetration.
Provided pricing solutions for transportation, optimizing supply chain costs and reducing expenses for multiple clients.
Built Pre-sales decks and Quotes.
Automated Data Loading & Formatting processes.
Conducted marketing and sales analysis, provided pricing solutions for transportation, automated data loading & formatting processes.
Built a Recommendation engine for an OTT app, resulting in 33% rise in click-through rates and a 25% improvement in overall watch time.
Analyzed user engagement and monetization strategies, increasing ad revenue by 21%, also managed data pipelines, automated and built reusable sql queries.
Acted as a Client liaison between business clients and technical teams, translating requirements and presenting insights.
Developed a market-mix model for e-commerce clients, optimizing marketing strategies and increasing ROI by 36%.
Conducted Festive Sale Pricing Analysis, revealing a ~30% revenue increase during Q3, 2017.
Worked on Data Scraping and Bug Tracking and error reporting, reducing error rates by 31%.
Configured and hosted Linux servers on AWS, used S3 buckets and SageMaker for model building, improving deployment efficiency.
Developed backend and frontend for e-commerce websites, enhancing user experience and functionality.
Built a Recommendation engine for an OTT app, analyzed user engagement, acted as a Client liaison, developed market-mix models.
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