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Dhruv S. — Mid-Level Data Analyst from United States

Dhruv S.

Mid-Level Data Analyst

United States 2-3 years
Open to offersNew to Platform
Languages
EnglishHindi
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About

Dhruv S. is a seasoned Data Analyst based in Jersey City, NJ, with more than three years of experience specializing in growth and marketing analytics. Currently, he is serving as a Data Analyst at the Delta Rising Foundation, a sustainability nonprofit, where he has been instrumental in creating a comprehensive GA4 and Looker Studio-based reporting system that tracks extensive user metrics. He has effectively managed a $400/day Google Ads budget to enhance CTR and has been key in flagging site restructuring needs. Previously, Dhruv led sales operations analytics for Echelon India in the real estate sector, where he increased lead-to-close rates by 12% through sophisticated Python-driven analysis. His contributions have consistently tied to impressive profit margins, with a $24M profit tied to analytical projects. Dhruv's technical skill set includes Python, SQL, Power BI, and Tableau, which he has effectively utilized across industries ranging from legal-tech B2B SaaS to hyperlocal commerce, demonstrating a remarkable aptitude in designing impactful BI solutions and optimizing data pipelines.

Experience

  • Data Analyst — Growth & Marketing

    Delta Rising Foundation · 2026 — Present
    Developed a weekly reporting system using GA4 and Looker Studio to monitor over 600 monthly users and campaign performance, transitioning from ad-hoc spreadsheets to an automated dashboard. Conducted an audit and restructuring of Google Ads campaigns within a $400/day budget by migrating keywords and addressing conversion tracking issues. Identified traffic issues and engagement problems on the donation page, leading to a site restructure in collaboration with the web team. Defined Ideal Customer Profiles (ICPs) and established Google Ads campaigns for a B2B carbon credit lead generation initiative. Set up Salesforce for tracking the lead pipeline, enabling visibility into conversion effectiveness across ICPs. Executed SEO keyword analysis for underperforming pages and coordinated UTM tagging with the social team for improved attribution.

  • Data Analyst — Sales Operations

    Echelon India · 2023 — 2023
    Served as the lead analyst for a 25-member sales and marketing team, executing stage-by-stage conversion analysis using Python (Pandas, NumPy) on over 1,000 Salesforce leads to identify bottlenecks in the sales funnel, with findings incorporated into the sales playbook. Automated ETL pipelines were built in Python and Airflow to extract data from Salesforce and other systems into S3, which were then loaded into Snowflake and utilized for Power BI dashboards tracking sales metrics. Additionally, regression models were developed in Python to aid pricing strategies across more than 50 neighborhoods, alongside cohort and marketing attribution analysis performed in SQL that optimized the allocation of marketing budget based on channel performance.

  • Founder

    Local Lift (Hyperlocal Quick-Commerce) · 2020 — 2023
    Developed time series forecasting models in Python to accurately predict demand across four product categories, facilitating effective inventory planning and delivery scheduling for a hyperlocal network. Analyzed user funnel data in Amplitude to understand the entire journey from acquisition to retention, identifying drop-off patterns that influenced product prioritization and fulfillment strategies. Successfully grew operations to over 40,000 orders through organic and referral channels without any paid marketing, and negotiated a partnership with a local retailer for last-mile delivery.

  • Data Analyst

    India Legal · 2021 — 2022
    Conducted a comprehensive analysis of the user journey from chatbot intake to payment for a legal marketplace featuring over 300 lawyers. Identified significant drop-off rates at the payment stage for both members and non-members, leading to A/B tests on display cards and pricing pages that decreased these rates. Segmented platform members into value tiers in SQL and Python (Pandas) based on spending and engagement, directly informing the recommendation engine for lawyer matches. Created Tableau dashboards integrating data from Google Analytics and internal sources to provide insights on lawyer performance, pricing, and specialization for both users and the internal team.

Skills & Expertise

AccountingData AnalysisData Analyst

Education

  • MS Business Analytics — Data Analytics Concentration
    Baruch College, CUNY · 2024 — 2025
  • BBA Business Administration — Economics Concentration
    GGSIPU · 2018 — 2021