Data Analyst Analytics

Tejas Padavalamane

Chicago, IL 312-***-**** *************@****.***.*** LinkedIn Portfolio Github SUMMARY

Results-driven Data Analyst with 3+ years of experience in data analytics, visualization, and performance reporting across IT services and sports analytics sectors. Proficient in SQL, Python, Power BI, and Tableau with a strong command of statistical modeling, ETL processes, and data storytelling. Demonstrated success in automating dashboards, improving data accuracy, and delivering actionable insights to drive strategic business decisions. EDUCATION

Illinois Institute of Technology, Chicago, IL Aug 2023 – May 2025 Master of Information Technology and Management — concentration: Data Analytics and Management, GPA 3.9/4.0

• Course work: Database Management system, R Programming for Data Analytics, Modern Data Warehouse, Data Mining and Machine Learning. K.S. Institute of Technology, Bengaluru, India Aug 2016 – Aug 2020 Bachelor of Engineering in Electronics and Communication, GPA 3.390 /4.0 TECHNICAL SKILLS

Programming & Data Analysis: Python, R, SQL, MySQL, Oracle, MS Excel

Data Visualization: Power BI, Tableau, ggplot2, Matplotlib

Data Manipulation & Libraries: Pandas, NumPy, Scikit-learn

Platforms & Tools: Microsoft Fabric, Synapse Data Engineering, Autosys, Splunk, Grafana, Nimbus, Power Platform

Statistical & Analytical Techniques: EDA, Hypothesis Testing, Linear Regression, ANOVA, A/B Testing, Time Series Analysis, Predictive Modeling

WORK EXPERIENCE

INFOSYS, Bengaluru, India Apr 2022 – Aug 2023

Data Analyst

• Reduced report generation time by 30% by developing advanced SQL queries to support ad-hoc analysis and operational reporting for business units.

• Improved system reliability by 25% by analyzing production support logs and proactively identifying performance bottlenecks using Grafana and Splunk.

• Enhanced stakeholder visibility by creating interactive dashboards and custom data extracts, streamlining internal reporting workflows across departments.

• Increased QA test efficiency by 20% by validating data integrity across environments using JIRA, while collaborating with QA and Dev teams during releases.

• Minimized incident response time by building real-time monitoring dashboards and automating alerting systems using Grafana, JIRA, and Procmon.

• Accelerated task resolution by 30% by optimizing the JIRA ticketing workflow, enabling faster turnaround on root cause analysis and support operations. HUDL India Pvt.Ltd., Bengaluru, India Jun 2021 - Mar2022 Data Analyst

• Achieved a 94% data accuracy rate by standardizing event tagging and implementing quality checks using Excel-based validation templates.

• Delivered over 2,000 structured performance datasets by analyzing sports footage using Excel, custom tagging tools, and video analysis platforms.

• Improved scouting and game-planning decisions for sports teams by designing Power BI dashboards to visualize key player and team metrics.

• Reduced data errors and rework by 25% by implementing a validation framework and collaborating with QA to maintain consistent analysis protocols.

• Enhanced product team decisions by translating raw in-game footage into structured datasets using event tagging, sports rules, and analytics models.

• Supported coaching staff and internal stakeholders by creating performance summary reports using Power BI, resulting in faster decision cycles. XYID Pvt. Ltd., Bengaluru, India Aug 2020 – Jun 2021 Data Analyst Intern

• Improved data processing speed by 15% by writing optimized SQL queries using DML operations structuring outputs in MS Excel for weekly business reports.

• Increased reporting efficiency by 30% by developing automated Excel and Power BI dashboards using data extracted via SQL, reducing reliance on manual reports.

• Enhanced schema reliability by modifying database structure using DDL commands to support accurate and consistent data reporting pipelines.

• Delivered actionable insights to business stakeholders by aggregating and transforming large datasets using SQL joins and Excel pivot tables. PROJECTS

Cryptocurrency OHLCV Dataset Prediction [Github]

• Achieved a 15% simulated annual return by building a real-time cryptocurrency forecasting system in Python, ingesting and processing minute-level OHLCV data.

• Improved forecasting accuracy by 70% through historical trend analysis using statistical models including SVM, Random Forest, GARCH, and T- distribution.

• Automated model backtesting and evaluation pipelines to optimize strategy selection and reduce manual testing time by 40%. Modern Data Warehouse Implementation [Github]

•Designed and implemented a modern data warehouse using Microsoft Fabric and the Medallion architecture (Bronze, Silver, Gold layers) to streamline analytics workflows.

• Developed ETL pipelines using Synapse Data Engineering, Notebooks, and Power BI to transform raw data into actionable business insights.

• Modeled datasets using semantic layer (star schema) and created interactive dashboards, enabling dynamic KPI reporting and improved data accessibility. Movie Rating Analysis (IMDB Dataset) [Github]

•Conducted Exploratory Data Analysis (EDA) and hypothesis testing with ANOVA, achieving 94% testing accuracy on IMDB movie ratings.

•Built and validated a linear regression model in R, improving rating prediction accuracy by 25%.

•Created data visualizations using ggplot2 (histograms, boxplots, overlay plots), enhancing interpretability of relationships between variables. CERTIFICATIONS

• Google Data Analytics Professional Certificate – Coursera

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