Power Bi Data Analyst

Venkatachalam Mallikeswaran

814-***-**** **************.**@*****.*** linkedin.com/in/mven github.com/M-Venkatachalam SUMMARY

Data-driven analyst with hands-on experience in building dashboards, automating reportingworkflows, and analyzing logistics KPIs to improve warehouse and transportation operations. Proficient in Power BI, SQL, and Python, with a track record of developing scalable data pipelines, ensuring data quality, and delivering actionable insights to cross-functional teams. Adept in transforming complex operational data into visualizations that support real-time decision making and continuous improvement. PROFESSIONAL EXPERIENCE

Human-Centered AI Lab, State College, PA: Research Assistant Jan 2025 - May 2025

• Investigated memory retrieval in Embodied AI agents to improve decision-making under partial observability, focusing on entropy, object salience, and temporal exposure in alignment with GenAI and cognitive modeling frameworks.

• Parsed 10,000+ timestamped action logs (JSON) using Python to extract cognitive features such as object type and observation duration.

• Created comparative visualizations using Python (Matplotlib, Altair) to evaluate agent performance and inform design decisions — collaborating with cognitive science researchers to align AI outputs with behavioral theories. Romark Logistics, Hazleton, PA: Data Analyst Intern Jun 2024 - Aug 2024

• Analyzed, transformed, and queried 150+ tables in Snowflake, integrating data from two distinct sources to support operational and logistics reporting.

• Designed and presented performance dashboards in Power BI and Excel to warehouse managers and cross-functional leads, enabling actionable insights on KPIs (line efficiency, cycle counts) and reducing manual reporting by 32+ hours/month.

• Developed a scalable data pipeline to standardize and report key operational and cost-related KPIs, enabling month-end reporting and cross-functional reviews for warehouse productivity and resource planning Square Shift Technologies, Chennai, India: Software Developer Intern Jan 2023 - Mar 2023

• Co-developed an internal Employee Management System (EMS) in an Agile team using Jira to manage sprints and issue tracking; collaborated with senior engineers and UI/UX designers to deploy features on GCP.

• Designed and embedded 5+ dynamic trend charts using data from 1K+ employee records; enabled real-time insights through backend optimization and cloud database integration. EDUCATION

Master of Science in Computer Science – Pennsylvania State University, University Park May 2025 Relevant coursework: Data Mining, Optimization Methods, NLP, Machine Learning and Pattern Recognition, Data Science Bachelor of Engineering in Computer Science – Anna University, India May 2023 Relevant coursework: Statistics, Linear Programming, Artificial Intelligence, Database Management, Algorithms RELEVANT PROJECTS

Flight Delay Analysis Using BTS & Weather Data

• Analyzed 5 years of U.S. flight data (1998–2002) from Bureau of Transportation Statistics and integrated with federal weather data, focusing on data cleaning, outlier handling, scaling, and binning.

• Performed hypothesis testing on post-9/11 TSA checks and built ML models (XGBoost, SVM), optimizing model parameters using gradient descent, achieving 90% prediction accuracy. Cloud-Based ETL Pipeline for Bike Sales Analytics

• Designed and automated a batch ETL pipeline to process 100K+ sales records using Apache Airflow, BigQuery, and Cloud Compute, supporting system-level data consistency and clean table delivery for reporting.

• Built Tableau dashboards on top of analytics-ready tables to visualize revenue, regional trends, and product performance — reducing manual analysis time by 40%.

Food Demand Forecasting Lion’s Pantry, Penn State

• Built time series forecasting models (ARIMA, Prophet) to project weekly demand and optimize inventory planning for 100+ essential items, reducing stockouts and supporting proactive budget allocation and resource optimization.

• Improved inventory reliability by 35% and minimized waste through data-informed cost control strategies, contributing to more accurate budget forecasts and enabling 2,000+ students and staff to maintain consistent access to essential resources. TECHNICAL SKILLS

Languages: Python, SQL, NoSQL, DAX, C/C++

Data Platforms & Tools: Snowflake, Google Cloud Platform (BigQuery, Cloud Compute), Azure Analytics, Apache Airflow Business Intelligence & Visualization Power BI, Tableau, Looker Studio, Excel (Advanced, VBA Macros) Analytics & Forecasting Time Series Forecasting (ARIMA, Prophet), Exploratory Data Analysis (EDA), KPI Tracking, Trend Analysis, Operational Dashboards

Machine Learning & Modeling: Predictive Modeling, Classification, Regression, Clustering, Deep Learning (TensorFlow), Ensemble Methods (Random Forest, XGBoost, Gradient Boosting) Core Competencies: Data Governance, Data Validation & Quality Control, Stakeholder Reporting, Structured Data Maintenance

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