Hariprasath Mahendran

Staff Data Analyst with 8+ years of experience in product analytics and data science, translating business challenges into actionable recommendations that improve the core product experience and drive growth, retention, and product strategy. Partnered with cross-functional teams (Product, Engineering, Operations) to enable data-backed decision-making and operational efficiencies.

Specialist — Marketing Analytics at FRESHWORKS (2024-07 – Present)

• Drove strategic analyses and presented data-driven insights to senior leadership, seamlessly translating complex datasets into actionable recommendations that optimized future planning and investment decisions in the form of weekly/bi-weekly/monthly reviews.
• Extracted insights from large data sets to refine attribution models across the customer journey, establishing end-to-end measurement that reduced measurement bias by 18% and accurately tracked conversion contributions.
• Designed and developed a Power BI dashboard to proactively surface comprehensive account intelligence by integrating account-based marketing (ABM) performance metrics and account-specific signals, enabling sales teams to effectively identify and target high-value user segments.
• Partnered with cross-functional teams to analyze the impact of user acquisition initiatives on customer conversion rates, lifecycle growth, and overall revenue generation.
• Designed and interpreted experiments to measure channel performance (e.g., analyzing the impact of pausing search ads), uncovering a 25% decline in top-of-funnel metrics and driving data-backed decisions to reallocate spend.
• Monitored and proactively surfaced trends across key business metrics including top-of-funnel session volume, signup-to-demo conversion rates, and regional campaign performance to evaluate landing page efficacy and optimize the broader user acquisition journey.
• Synthesized complex datasets to evaluate budget-versus-actuals, segment-level booking goals, and SEM budget allocations, managing comprehensive data deliverables for executive business reviews to inform quarterly demand generation strategies.

Senior Analyst at LATENTVIEW ANALYTICS (2020-10 – 2024-06)

• Developed and deployed a regression model in Python to predict Gross Bookings and merchant churn. The model contributed ~$300K in monthly revenue by preventing churn for ~20 high-profile merchants for a B2C Marketplace client.
• Restructured and optimized merchant lifespan calculations using advanced statistical techniques such as the Geometric Distribution, leading to adoption by regional teams for LTV estimation and subscription fee modeling.
• Engineered data warehouse by transforming raw Salesforce data into structured, accessible tables, enabling analysts to efficiently access clean data for downstream BI tools.
• Developed Tableau dashboards to present results of process automation and automated insight generation, providing leadership with actionable KPIs and streamlining decision-making processes.

Analyst at LATENTVIEW ANALYTICS (2019-04 – 2020-09)

• Automated product categorization using deep learning (CNN) and NLP pipelines, cutting manual effort by 2 weeks per cycle and improving categorization accuracy to 80%.
• Utilized NLP and fuzzy matching techniques, alongside Random Forest and SVM, to automate text classification for product categorization. Improved the volume of categorized products by 74% with 90% accuracy.
• Created Power BI reports to track product performance and communicate seasonal findings to senior management, enhancing insights into customer purchasing patterns and driving strategic decisions.

Analyst at IBM (2016-06 – 2017-06)

• Worked extensively with SQL Server for backend development, including advanced SQL tasks such as writing functions, views, triggers, and maintaining process flow, ensuring data quality and operational efficiency.

Post Graduate Program in Data Science and Engineering – Great Lakes Institute of Management (2019-03)

Bachelor of Engineering in Electrical and Electronics – PSG College of Technology (2016-05)