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Mohith Reddy Seelam

Data Analyst • Baltimore, MD • s*************@gmail.com • 980****590 • linkedin.com/••••• • mohithseelam.info/•••••

Professional Summary

Data Analyst with 2+ years of experience building data pipelines, dashboards, and validation systems using Python, SQL, and BI tools to improve reporting accuracy and operational efficiency. Skilled in anomaly detection, predictive modeling, dbt testing, and translating data into executive-ready insights that drive compliance and business decisions.

Technical Skills

Programming Languages: Python
Frameworks and Libraries: pandas,NumPy,scikit-learn,PyTorch
Databases: PostgreSQL,Snowflake,Google BigQuery,SQL,Apache Spark,Databricks,ETL Design,dbt,Data Quality Assurance
Cloud and DevOps: Microsoft Azure,AWS S3,Jupyter Notebook,Power Automate,Power Apps,Google Sheets
Data and Analytics: Power BI,DAX,Tableau,Looker,Amazon QuickSight,Google Data Studio,Streamlit,Executive Reporting,Dashboard Development,Excel
Tools and Methodologies: Git,JIRA
Skills: statsmodels,NLP,Time-Series Analysis,Predictive Modeling,Anomaly Detection
AI & ML: LLM's,Vector Database,Chat GPT(GPT models),Claude,Image classification,Computer vision,LangChain,Supervised & Unsupervised Learning,Model Optimization

Work Experience

Saayam for All
San Jose, CA (Remote)
Database Volunteer
Feb 2026 – Present
Volunteer role supporting a nonprofit's financial disbursement and donor reporting by building live BI reports and data validation processes.
Tech Stack: Power BI, Snowflake, PostgreSQL, Python, pandas, DAX, dbt concepts
  • Built Power BI DirectQuery reports connected to Snowflake disbursement tables to enable same-day anomaly detection, accelerating compliance reviews for financial disbursements.
  • Authored complex PostgreSQL CTEs joining donor and disbursement tables to produce an auditable financial dataset used for quarterly budget planning decisions.
  • Automated ETL data validation in Python using pandas to detect malformed records; flagged 28% of incoming records and reduced monthly financial close time by 35%.
  • Designed DAX-based threshold alerts and KPIs in Power BI to surface exceptions and recurring issues, eliminating several recurring audit findings.
  • Implemented data freshness and schema checks (dbt-style logic) to prevent stale or malformed loads into Snowflake, improving reporting reliability for stakeholders.
  • Collaborated with finance and compliance stakeholders to translate reporting requirements into dashboard drill-throughs and filters, improving approval cycle times.
Kent State University, Dept of Arts & Science
Kent, OH
Research Assistant
Aug 2024 – Dec 2025
Academic research role producing enrollment, grant, and financial datasets and dashboards to support institutional reporting and federal compliance.
Tech Stack: PostgreSQL, Power BI, Amazon QuickSight, Python, pandas, statsmodels, dbt concepts
  • Consolidated multiple enrollment and finance sources with PostgreSQL CTEs and window functions to produce audit-compliant datasets, cutting HR reporting time by 50%.
  • Developed Power BI and Amazon QuickSight dashboards with drill-through filters and DAX measures to centralize grant performance tracking and monitor federal compliance.
  • Performed cohort analysis and OLS regression using pandas and statsmodels to identify program risk trends; findings influenced academic program restructuring.
  • Implemented dbt schema tests and freshness checks on upstream datasets to prevent integrity failures and ensure timely compliance reporting windows.
  • Automated data extraction and transformation tasks with Python scripts to standardize ingestion, reducing manual wrangling time for researchers by 40%.
  • Prepared reproducible analysis and documentation for grant teams to support additional federal funding requests, improving transparency of data lineage.
GVR Solutions LLC
Maryland, US (Remote)
Data Analyst
Mar 2023 – Jan 2024
Provided analytics and BI for an engineering/IoT-focused services company; converted telemetry and equipment logs into actionable insights for budgeting and contracts.
Tech Stack: Power BI, DAX, SQL Server, Great Expectations, scikit-learn, statsmodels, Power Automate, Power Apps
  • Designed Power BI dashboards using DAX over SQL Server IoT telemetry to replace Excel models; dashboards became the primary tool for capital budget approvals within two months.
  • Applied Great Expectations constraints to equipment runtime and failure logs to automate data quality checks, reducing manual QC efforts by 40% during sprints.
  • Modeled equipment degradation with scikit-learn linear regression and statsmodels OLS to quantify lifecycle trends; results informed pricing strategy and contract renewals.
  • Optimized telemetry ETL and SQL queries to improve data refresh performance, enabling near real-time KPIs that reduced decision latency for operations teams.
  • Configured Power Automate workflows integrated with Power BI KPIs and Power Apps dashboards to trigger delinquency alerts, reducing contract follow-up time by 30%.
  • Collaborated with engineering and finance to translate technical telemetry metrics into executive-facing KPIs used for capital expenditure planning.
Credo Systemz
Chennai, India
Data Analyst Intern
Sep 2021 – Mar 2022
Internship at an IT services firm supporting government and financial reporting through query optimization, data validation, and pipeline improvements.
Tech Stack: PostgreSQL, Python, pandas, SQL, EXPLAIN ANALYZE
  • Improved data accuracy by 25% through complex PostgreSQL multi-table JOINs and anomaly-flagging logic, enabling timely resolution of stalled financial close processes.
  • Optimized PostgreSQL query performance by 40% with composite indexes, CTE refactoring, and EXPLAIN ANALYZE-driven tuning to accelerate governance submissions.
  • Developed Python IQR-based outlier detection at ingestion to catch anomalous values and achieve zero audit rework on compliance submissions.
  • Refactored ETL patterns to eliminate full-table scans and reduce pipeline runtime, improving analyst productivity and on-time government reporting.
  • Created reusable SQL templates and documentation for analysts to standardize reporting and reduce ad-hoc query burden across teams.
  • Collaborated with QA and reporting teams to validate transformed datasets against source systems and maintain end-to-end data lineage.

Projects

NFL Game Outcome Prediction System
Tools Used: Python, pandas, scikit-learn, Streamlit, Predictive Modeling
  • Built an end-to-end win-probability system ingesting play and historical game data, performing feature engineering and model training to estimate win probabilities.
  • Developed a Streamlit dashboard to visualize game predictions and betting insights, enabling interactive exploration of model factors and confidence.
Historical Analysis and Prediction of Tesla's Stock Performance
Tools Used: Python, SQL, pandas, Logistic Regression, Feature Engineering
  • Analyzed historical stock and financial metrics, engineered features and trained logistic regression models achieving 76.6% prediction accuracy on held-out test splits.
  • Documented preprocessing and modeling steps to ensure reproducibility and explainability of predictions for financial-analysis stakeholders.

Education

Kent State University
Master of Science, Data Science • Kent, OH, USA • Jan 2024 – Dec 2025
Sathyabama Institute of Science and Technology
Bachelor of Engineering, Computer Science and Engineering • Chennai, India • Jun 2019 – May 2023

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