Akram Pathan
Jersey City, NJ - *****, USA +1-516-***-**** ***************@*****.*** LinkedIn GitHub SUMMARY
Data Analyst with 3+ years of hands-on experience, holding a Master’s degree in Data Science from Stevens Institute of Technology. Proficient in advanced analytical techniques, forecasting, data visualization, and cloud technologies. Managed large-scale financial and sales data, developed interactive dashboards, and optimized data processes across industries. Experienced in Python, SQL, R, and database systems, with expertise in AWS and Azure cloud platforms. Communicates complex data clearly for strategic decision-making and collaborates with teams to meet project milestones. TECHNICAL SKILLS
Programming Languages: Python, SQL, R, SAS
Databases/ Libraries: MySQL, Oracle, Microsoft SQL Server, PostgreSQL, MongoDB, NumPy, Pandas, Matplotlib, Seaborn, Plotly
Cloud Technologies: AWS (EC2, S3, RDS, Lambda, Redshift, CloudWatch), Azure (Blob Storage, Data Lake, Data Factory), Google Big Query, Snowflake
Machine Learning & AI Frameworks: TensorFlow, PyTorch, Scikit-learn, NLTK, LangChain Data Visualization: Tableau, Power BI, MS Excel, Amazon Quicksight, Looker Data Analysis & ETL Expertise: Data Mining, Data Cleansing, Statistical Analysis, Data Wrangling, Data Warehousing, Alteryx Method & Version Control: Agile, Waterfall, Git, GitHub PROFESSIONAL EXPERIENCE
Data Analyst, Dow Jones Princeton, NJ Jan 2025 – Present
● Analyzed 8M+ records using BigQuery SQL to detect patterns and uncover insights that informed strategic decisions and enhanced AI models.
● Automated data analysis workflows by developing Python scripts to optimize SQL queries for data insertion, improving integration speed and accuracy by 40%, and eliminating data pipeline bottlenecks.
● Validated data extracted from PDFs using Amazon S3, resolving discrepancies to ensure 100% accuracy and integrity in datasets.
● Engineered and deployed Looker dashboards to classify large-scale content data, identifying trends, improving relevancy, and accelerating approval workflows.
● Built dynamic Google Sheets reports to track project progress, approvals, and content issues, using trends to improve decision-making and enhance collaboration.
● Refined OCR-based text extraction models in collaboration with product leadership and the AI/ML team, increasing classification accuracy by 25% and aligning results with business goals. AI Product Designer/Analyst Intern, Radical AI New York, NY Sep 2024 – Dec 2024
● Analyzed user behavior and chatbot interaction data using Python and SQL, performing cleaning, transformation, and feature extraction to enhance insight accuracy and usability.
● Crafted and delivered 3+ interactive Tableau dashboards, visualizing behavioral patterns to help product teams identify user friction points and prioritize improvements.
● Collaborated with UI/UX designers and software engineers to translate analytical findings into actionable design changes, improving chatbot usability and alignment with user needs.
Data Analyst, KPMG India Sep 2020 – Jul 2022
● Consolidated financial data from transactional databases, accounting systems, and financial reporting platforms into a unified repository, managing over 1 million records to ensure comprehensive data coverage.
● Engineered and implemented complex SQL queries to extract, merge, and integrate financial data into Oracle databases, ensuring 100% data completeness and accuracy across all datasets.
● Harnessed pandas for data manipulation and merging, creating 20 new financial metrics that enhanced performance analysis and supported more accurate decision-making.
● Developed interactive Power BI dashboards utilizing DAX to create custom KPIs, time intelligence measures, and financial insights on revenue growth, expense variance, and profitability, enhancing stakeholder decision-making by 30%.
● Built dynamic Excel reports using pivot tables, VLOOKUP/XLOOKUP, conditional formatting, and advanced formulas to summarize trends and deliver 15+ analytical reports monthly with accurate, actionable financial insights.
● Orchestrated AWS services (EC2, S3, Lambda, RDS, Redshift) for scalable computing, secure storage, serverless processing, data warehousing, optimizing data handling, and complex queries.
● Led agile project life cycles and utilized GitHub for version control, ensuring timely delivery of financial analysis objectives and maintaining data integrity across 5+ projects through effective collaboration with cross-functional teams. Data Analyst Intern, Trigent Software India Mar 2020 – Aug 2020
● Constructed automated Python scripts to extract, transform, and analyze sales data from diverse sources; achieved a significant reduction in processing time by 50 hours monthly while enhancing overall workflow efficiency.
● Designed and optimized MySQL databases to store and manage large volumes of sales data, implementing indexing strategies and query optimizations that maximized data retrieval speed.
● Created comprehensive, interactive dashboards and reports using Power BI and MS Excel, translating intricate sales data patterns into visually compelling presentations that elevate data-driven decision-making across sales departments.
● Managed code repositories for sales data analysis project using Git, tracking changes, and maintaining code quality throughout development lifecycle of 12 analytical models and data pipelines. EDUCATION
Master of Science in Data Science, Stevens Institute of Technology Hoboken, NJ Sep 2022 – May 2024 Bachelor of Technology in Computer Science, Rajarambapu Institute of Technology India Aug 2017 – May 2021 PROJECTS
Time Series Modeling for Financial and Meteorological Forecasting
● Forecasted stock prices and managed risk by applying ARIMA and GARCH models to 9 years of TCS stock price data, enabling data-driven insights for strategic decision-making using Python.
● Achieved 95% forecast accuracy by applying SARIMA to analyze Seattle's daily weather patterns, supporting data-driven strategic planning in weather-dependent scenarios.
Customer Sales and Pricing Strategy Analysis
● Analyzed 300,000+ entry dataset in Tableau to calculate revenue across dimensions, evaluating sales volume against discounts for 200+ products, which informed targeted marketing strategies and boosted profit margins.