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Swetosree Sinha

@swetosreesinha

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Senior data analyst translating ambiguity into KPIs, operational process improvements, and automated dashboards.

United States

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What I'm looking for

I’m looking for a role where I can lead analytics roadmaps, turn ambiguous needs into measurable KPIs and operational workflows, and deliver automated SQL + BI reporting—while applying LLM/AI methods for faster, higher-impact insights across stakeholders.

I’m a data analytics professional with 10 years of experience translating ambiguous business problems into operational processes, KPIs, and reporting infrastructure across eCommerce, supply chain, and enterprise operations.

I’ve led end-to-end strategy and operations analytics programs, including owning roadmaps that drove 95% on-time delivery of cross-functional projects. In customer and commerce contexts, I’ve helped reduce support dependencies by 3.7%, improved SMB product adoption by 6.8%, increased LTV by 8%, and reduced churn by 5%.

I build scalable data models and automated BI reporting in SQL and tools like Tableau and Power BI, saving 10+ hours/week while improving data quality and integrity by 17%. I also leverage Large Language Models (LLMs) and AI-powered analytics to automate analysis of unstructured datasets and accelerate anomaly detection and stakeholder insights.

Experience

Work history, roles, and key accomplishments

Current

Sr. Data Analyst - Customer Success

Current

Unify Consulting

Apr 2025 - Present (1 year 4 months)

Translate customer engagement data into product and process recommendations, reducing support dependencies by 3.7%. Improve SMB product adoption by 6.8% by redesigning the customer experience journey and supporting operational workflows.

Customer Engagement Analytics Customer Success Funnel Analysis Stakeholder Management Data Driven Strategy

Sr. Data Analyst - Strategy & Ops

Albertsons

Jul 2023 - Apr 2025 (1 year 9 months)

Led end-to-end strategy and operations analytics across inventory, order, and user demographic data, implementing a labor-planning model based on sales, inventory, and market trends. Increased LTV by 8%, reduced churn by 5%, and owned the analytics roadmap delivering 95% on-time completion of strategic operations projects.

Operational Analytics Labor Planning Forecasting Inventory Analytics Customer Segmentation Profitability Analysis LTV Power BI BI Reporting

Sr. Data Analyst - Meta Supply Chain

Meta (Vendor)

Feb 2023 - Jun 2023 (4 months)

Built SQL data models using Presto and supply chain management (SCM) views, defining KPIs from Bill of Materials (BOM) data. Developed Tableau reporting for managers to support performance and ROI decisions.

SQL Presto Data Modeling Supply Chain Management Bills Of Materials (BoMs)KPIs Tableau BI Reporting

Sr. Data Analyst - Google Supply Chain

Google (Vendor)

Feb 2020 - Jan 2023 (2 years 11 months)

Led analytics operations for Google’s data center construction supply chain, building SQL data models and dashboards for cross-functional stakeholders. Improved infrastructure data quality by 17% and automated scalable BI reporting, saving 10+ hours per week while providing real-time operational visibility.

SQL Data Modeling Dashboarding Data Quality

Data Analyst - Admin Reporting

University of Illinois Urbana-Champaign

Sep 2019 - Feb 2020 (5 months)

Built SQL-based reporting for administrative data and automated satisfaction-survey dashboards in Tableau. Improved team revenue by 3% through process mapping and operational automation.

SQL Reporting Tableau Data Reporting Process Mapping Automation

Data Analyst Intern

CME Group Inc

May 2019 - Aug 2019 (3 months)

Cleaned and normalized market data at scale and used Python to visualize and evaluate key market-health metrics. Built time-series models to detect anomalies, forecast trends, and surface operational insights.

Python Time Series Modeling Anomaly Detection Forecasting Data Visualization

Oracle & SQL Database Admin/Dev

Accenture

Jul 2012 - May 2017 (4 years 10 months)

Improved response time across 14 databases by 28% by resolving telecom operational problems with well-managed data solutions. Enhanced database performance by up to 13.5% by reducing manual intervention through SQL process automation.

Oracle SQL Database Administration