Data Analyst • Chicago, IL • linkedin.com/••••• • drivetube.ai/•••••
Professional Summary
Data Analyst with 6 years of experience delivering analytics, reporting, and data engineering across pharmacy claims, revenue cycle, supply chain, and subscription billing. Strong in SQL and Python for large-scale data processing, Snowflake and Snowpark for cloud ELT, and dbt Core and Apache Airflow for reliable pipelines. Built Power BI semantic models and DAX measures and produced Tableau dashboards that operations and finance leaders rely on for daily decisions. Experienced diagnosing issues in 5M+ claims datasets and operating 100+ weekly Airflow DAGs to reduce pipeline failures and support on-the-ground remediation. Comfortable owning work from raw ingestion through transformations to production dashboards, translating stakeholder requirements into testable metrics, and standardizing reconciliation and data quality to reduce manual work and cycle time.
Technical Skills
Programming Language: Python,R,SQL
Databases: Snowflake
Cloud Platforms: AWS
Version Control & Development Tools: Git,Jira
Data Engineering & Processing: Snowpark,Apache Airflow,dbt
Supported pharmacy operations, revenue cycle, inventory, and compliance analytics at a national retail pharmacy; built pipelines and dashboards used by claims, store and distribution center, and compliance teams.
Tech Stack: Snowflake, Snowpark, SQL, Python, Power BI, DAX
Reduced claims adjudication dispute resolution cycle time from 5.1 to 4.2 business days across a 60-analyst cohort over six months by replacing manual spreadsheet cross-referencing with automated discrepancy flags and a centralized Power BI work queue.
Isolated top rejection drivers across NDC, prior authorization, and pricing logic by analyzing 5M+ adjudication and reimbursement records using SQL and Python, delivering weekly root-cause dashboards that sequenced aged exceptions for remediation.
Rebuilt third-party invoice reconciliation by authoring Snowflake SQL transforms to match vendor invoices, payment postings, and chargebacks and standardizing validation checks to improve first-pass acceptance and collections.
Automated inventory variance analytics across receiving, counting, ordering, and returns transactions to surface vendor overage and shortage patterns for 120+ high-volume SKUs using SQL, enabling prioritized corrective actions by store and DC leaders.
Prioritized DSCSA serialization remediation by analyzing 2D barcode and EPCIS event mismatches with Snowpark Python, producing ranked remediation worklists by estimated financial exposure and compliance risk.
Migrated legacy reconciliation extracts into Snowflake and refactored ingestion logic with Snowpark Python to standardize downstream marts and reduce manual extract maintenance.
Built Power BI semantic models and DAX measures consumed by operations and finance teams for daily monitoring and exception management.
Bytes Technolab Inc.
India
Data Analyst
Sep 2021 – Sep 2023
Delivered multi-tenant data engineering and reporting for e-commerce and subscription billing clients; maintained pipelines, implemented modular transformations, and built client-facing dashboards.
Maintained 100+ weekly Apache Airflow DAG runs across multi-tenant accounts, auditing dependencies and retry logic to eliminate overnight pipeline failures before client business hours.
Replaced fragile standalone SQL transformation scripts with modular, version-controlled dbt Core models to separate raw staging from curated marts and reduce downstream breakages.
Implemented dbt data quality tests for not-null, unique keys, and referential integrity to block malformed records from reaching production reporting.
Diagnosed slow AWS Redshift queries by analyzing system tables and execution plans, then partnered on distribution and sort key remediation to restore report performance.
Built SQL extracts and Tableau reporting layers for e-commerce and subscription billing dashboards, defining metrics directly with client stakeholders and reducing ad-hoc reporting requests.
Integrated dbt model development with Git and documented runbooks to standardize deployment and rollback procedures across client environments.
Bytes Technolab Inc.
India
Business Analyst
Sep 2018 – Sep 2021
Led product and billing analysis for subscription billing and customer portal projects; authored requirements, acceptance criteria, and finance/operations dashboards for client teams.
Tech Stack: Jira, Tableau, Excel, Power Pivot
Owned business analysis for subscription billing and portal builds, mapping signup through authorization, recurring invoicing, dunning, and cancellation into 60+ Jira user stories for engineering.
Authored business and functional requirement documents and acceptance criteria, and ran discovery workshops with client finance and product stakeholders to align scope.
Validated tax calculation, discount code, and multi-tier billing logic by authoring test scripts and executing user acceptance testing across release sprints prior to production cutover.
Replaced manual monthly spreadsheet billing with an automated recurring invoicing workflow and built the Tableau dashboard finance leadership used to track monthly recurring revenue, active subscribers, and aging invoices.
Built Power Pivot and Excel operational models to measure checkout funnel drop-off and conversion, quantifying where users abandoned multi-step flows for product and UX teams.
Coordinated sprint reviews and acceptance validation across engineering and QA to ensure delivered features met client accounting and compliance requirements.
Ingested 8,250 cryptocurrency asset snapshots from the CoinGecko API using paginated requests, retry logic, and rate limit backoff implemented in Python.
Produced 8,242 analysis-ready records by removing invalid and duplicate rows, standardizing symbols and timestamps, and engineering liquidity and stablecoin features with Pandas.
Built 10 Snowflake SQL views covering market capitalization, liquidity, 24-hour volatility, all-time high drawdown, market segments, and top gainers and losers.
Chicago Retail Theft Risk Analytics
Tools Used: Python, Pandas, XGBoost, Tableau
Analyzed Chicago crime records from 2001–2025 across temporal and location dimensions using Pandas to identify peak retail theft exposure by hour, weekday, and seasonal month.
Reached 66.3% arrest classification accuracy with XGBoost by engineering time and store-type features and benchmarking against logistic regression and random forest baselines.
Consolidated theft trends, arrest outcomes, and geographic hotspots into an interactive Tableau dashboard for retail loss prevention stakeholders.
Customer Cohort and Credit Risk Modeling
Tools Used: R, Python, SQL
Built customer retention cohort matrices in R with dplyr and ggplot2 to analyze repeat purchase velocity and retention decay at 30/60/90-day intervals.
Measured promotional lift using two-sample t tests and chi-square tests to isolate discount-driven one-time buyers from repeat purchasers.
Modeled credit default risk using logistic regression and decision trees, comparing precision-recall tradeoffs across approval thresholds.
Education
DePaul University
Master of Science, Business Analytics (STEM) • Chicago, IL • Sep 2023 – Mar 2025
SRK Institute of Technology
Bachelor of Technology, Computer Science and Engineering • India • Sep 2014 – Apr 2018
Achievements
Governing Clinical AI in Obstetrics: A Review of Safety Gaps and a Lifecycle Framework — 2026: IEEE publication reviewing 48 clinical AI systems (PRISMA) and proposing a lifecycle governance framework addressing model drift, bias auditing, and post-market monitoring gaps.
Powered by Drivetube · Create your own profile at drivetube.ai
Everything on Drivetube
Six products, two of them free forever. Start wherever you are.
at drivetube.ai/in/your-name: one true standard resume with a Hiring Snapshot (visa status, expected salary, notice period, work preference, relocation), an ATS-ready PDF download and a single shareable link. Free forever; interview requests come from verified employers and your contact details stay masked until you accept.
verified openings crawled ATS-by-ATS from 115,000+ real company career pages across 54 ATS platforms. Shows the true posting date from the source ATS — not when a listing was indexed — and deletes every general listing 3 days after it was actually posted. No ghost jobs, no ad-sponsored listings, no staffing reposts, no account needed.
human-written, ATS-optimised resumes by senior career writers, from ₹499.99 / $25.99. Available in every country, written to the destination country's own standard — a US resume, UK CV, German Lebenslauf and Indian resume are genuinely different documents. A paid service, separate from the free Drivetube Profile.
Daily matched jobs, tailored resumes, or we apply for you
Drivetube's paid service. Community sends daily Jobsheets of fresh jobs matched to your profile on WhatsApp and email, with the Drivetube Community ($39.99 for 3 months or $69.99 for 6 months; ₹999 or ₹1,899 in India). Jobhunt is one-time application credits with Community included: one credit tailors one resume and its cover letter (100 for $99 with 3 months of Community, 250 for $199 with 6 months). Let Us Apply is an add-on to Jobhunt: a human expert applies 250 times for you on your credits ($0.60 each, $150). Everything lives on one dashboard at drivetube.ai/drivetubeone.
hiring with no job postings and no applications. Paste your real job description and AI matches it against candidates' true standard resumes, returning ranked candidates with a match %, matched and missing skills and written reasoning. Free tier included; employers pay, candidates never do.
every product explained in full, with feature-by-feature comparisons against the job boards, AI apply tools, resume services and hiring platforms people actually use.
tactical job-search guides. Each post is one named tactic with the situation it applies to, the exact steps, a copy-paste message and honest failure modes. Free, no account.
The job board covers the United States, India, United Kingdom, Canada, Europe and Australia, and Resume Writing Services are available in every country.
Pricing is identical on the web, iOS and Android — no app-store markup. Monthly Community membership is purchased in the iOS app only; the website sells annual plans. The Android app has no in-app purchase, so Android members subscribe on drivetube.ai and then sign in to the app with full access. Membership follows your account, not your device.
