Data Analyst Analysis

Abhijeet Kumar Data Analyst

Washington, USA (Open to relocation) +1-425-***-**** *************@*****.*** LinkedIn SUMMARY

Data Analyst with 4+ years of experience transforming complex datasets into actionable insights to support strategic decision- making. Proven track record in data wrangling, statistical analysis, and dashboard development using tools such as SQL, Python, Excel, and Tableau. Adept at collaborating with cross-functional teams to identify business opportunities and optimize operational efficiency. Leveraging data to drive business value and committed to continuous learning in data science and analytics. TECHNICAL SKILLS

Data Analysis & Statistics: Data Wrangling, Exploratory Data Analysis (EDA), Hypothesis Testing, Statistical Modeling, A/B Testing, Regression Analysis, Root Cause Analysis, KPI Development & Tracking Technical Tools & Programming: SQL (PostgreSQL, MySQL, SQL Server), Python (pandas, NumPy, matplotlib, seaborn, scikit- learn), Excel (Pivot Tables, VLOOKUP, VBA), R, Git/GitHub Data Visualization & BI Tools: Tableau, Power BI, Looker, Google Data Studio, Plotly Databases & Data Management: Relational Databases, Data Warehousing (Snowflake), ETL Tools (Airflow, DBT), Data Cleaning, API Data Extraction, Web Scraping

Cloud & Platforms: AWS (S3, Redshift), Google Cloud Platform (BigQuery), Microsoft Azure Business & Communication: Data-Driven Decision-Making, Stakeholder Engagement, Dashboard Development, Cross-Functional Collaboration, Agile/Scrum Methodologies

PROFESSIONAL EXPERIENCE

Data Analyst, Uber, Washington, USA May 2024 – Current

Analyzed a large number of trips and rider behaviour records across 3 key metropolitan regions using SQL and Python, identifying geographic inefficiencies that managed to reduction in wait times through targeted driver rebalancing initiatives.

Designed and maintained 5+ interactive dashboards in Tableau and Looker for cross-functional teams, enabling near real-time tracking of operational KPIs such as rider wait time, driver idle time, and cancellation rates.

Automated manual reporting pipelines by developing modular scripts in Python and scheduling through Apache Airflow, which reduced weekly reporting effort by 6+ hours and decreased error rates.

Conducted advanced A/B testing on dynamic pricing models using Python (statsmodels) and internal experimentation platforms; analysis led to a 7.8% increase in revenue per active driver.

Extracted, cleaned, and merged large datasets from internal databases and third-party APIs using SQL, Python, and AWS Glue, increasing data processing accuracy and accelerating campaign targeting workflows.

Partnered with operations and logistics stakeholders to develop a time-series forecasting model for ride demand, improving vehicle allocation planning and reducing idle driver hours by 18% across peak shifts.

Collaborated with data engineering team to build scalable queries for experimentation analysis and geospatial clustering, enabling product managers to prioritize new feature rollouts based on actual usage patterns.

Documented all data pipelines, KPIs, and dashboard logic in Confluence to improve onboarding and team knowledge retention, reducing handover time for new analysts.

Data Analyst, iConsult Collaborative, New York, USA Feb 2023 – May 2024

Built and maintained 15+ custom dashboards in Power BI and Excel for multiple financial service clients, facilitating real-time monitoring of operational KPIs and enabling stakeholders to reduce monthly report generation time.

Used SQL, Python, and Excel to analyze client-side transaction datasets exceeding 5 million rows, identifying suspicious activity patterns and contributing to the prevention of fraud worth $5 M annually.

Developed and documented scalable ETL pipelines using Informatica to automate ingestion of structured and semi-structured data from 6 different sources, improving end-to-end data accuracy and reliability.

Conducted detailed root cause analysis on missed SLA targets by reviewing logs, scripts, and process flows; identified and remediated 3 recurring bottlenecks, leading to a 25% decrease in turnaround time for key workflows.

Directed the design and implementation of data quality frameworks across 3 major projects, introducing validation layers and anomaly detection scripts that flagged inconsistent data entries with high accuracy.

Coordinated with cloud engineering teams to migrate 2TB+ of legacy client financial data into a cloud data warehouse using AWS Redshift, reducing query latency by 45% and enabling faster insights generation.

Regularly translated analytical findings into business insights and presented them to client stakeholders during monthly review meetings, directly influencing roadmap planning and quarterly investment decisions.

Deployed Power Automate workflows for data integration, resulting in a 30% reduction in transfer errors and a 25% decrease in data discrepancies due to improved error handling mechanisms. Cloud Data Engineer, Acefone Software Private Limited, Haryana, India Jan 2020 – Jul 2022

Extracted, cleaned, and transformed over 2 million rows of raw transactional and customer data per month using complex SQL queries and pandas, improving team productivity.

Developed and deployed more than 15 interactive Tableau dashboards for business and product teams, automating key metrics tracking and cutting down weekly reporting time for operations team.

Automated recurring Excel reporting workflows using advanced formulas and VBA scripting, decreasing manual reporting workload by over 10 hours per week and reducing data input errors.

Collaborated with product managers, marketing analysts, and operations leads to define, refine, and monitor over 10 performance indicators (KPIs), enabling data-backed decisions in product lifecycle and customer retention strategies. EDUCATION

Master of Science, Information Systems May 2024

Syracuse University, USA

Bachelor of Technology in Electronics and Communication Engineering May 2020 Dr. A.P.J. Abdul Kalam Technical University, India

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