Hyderabad, Telangana, India
Analytics professional with experience across product, digital and advanced analytics, working at the intersection of data science, forecasting, and business decision-making. I specialize in leveraging SQL, Python, Adobe Analytics, Excel and Predictive Modelling to uncover actionable insights that drive business growth and operational efficiency. My experience includes demand forecasting, predictive modeling, and statistical analysis to understand product performance and customer behavior. I partner closely with stakeholders to translate complex data into clear, actionable recommendations that support planning, retention, and optimization strategies, enabling organizations to make informed, data-driven decisions.
• Defined and forecasted key product usage metrics for Tax & Accounting products using Prophet, SARIMAX, Exponential Smoothing and XGBoost, achieving 80–95% accuracy, to mitigate risk of server failure during peak usage. • Partnered with BI to automate recurring forecasting pipelines, reducing manual effort by 90% and ensuring consistent, scalable delivery of insights across product lines. • Developed a churn risk framework combining rule-based churn risk scores (e.g., license expiry, usage thresholds) with ML churn probability models (Logistic Regression, Random Forest, XGBoost), enabling accurate firm-level risk classification and churn timeline prediction. • Automated monthly churn model deployment in AWS with Snowflake + Power BI dashboard, improving retention by 2% YoY and reducing manual churn analysis by 90%. • Identified drivers of churn and underperforming product features, translating model insights into product roadmaps and customer success actions. • Scaling churn and retention analytics to document management and cloud-based products, supporting annual revenue targets and feature adoption strategies.
• Provided analytics support to a multinational telecommunication conglomerate to improve customer experience on websites and to unlock potential opportunities for website optimization and customer conversions. • Created insightful dashboards in Adobe Analytics to help stakeholders understand different customer journeys on • website based on their respective business requirements. • Reported on cross-sell effectiveness across web and app channels, providing recommendations that influenced growth strategy for existing customers. • Collaborated with implementation team to ensure accurate data capture by the web analytics tool, improving reliability of product usage tracking and experimentation. • Supported migration of legacy reports and Adobe segments to a new Report Suite, ensuring consistency and continuity of customer data. • Generated daily KPI insights for new FIOS customers, enabling leaders to monitor adoption and performance trends.
• Supported an international sportswear brand in optimizing eCommerce product performance and customer journeys, driving improved adoption and sales conversion across global regions. • Conducted benchmarking and KPI analysis across markets, delivering recommendations that identified an estimated €10M revenue uplift opportunity by improving funnel performance and conversion rates. • Investigated drivers of high product-page bounce rates using exploratory data analysis and predictive models (Logistic Regression, Decision Trees), validating hypotheses around price, size availability, and product attributes; insights directly informed product merchandising strategy. • Created standardized business performance reporting frameworks in Adobe Analytics to ensure consistency and actionable insights across teams. • Delivered category and campaign performance reports for emerging markets, identifying growth opportunities and evaluating effectiveness of marketing campaigns on key KPIs.