---
title: "Cherishma Reddy V. - Data Scientist in Justin | Tal"
description: "Meet Cherishma Reddy V., Data Scientist & Analyst | SQL · Power BI · Python · Machine Learning | M.S. Data Science, UNCW | Open to Work based in Justin."
image: "https://tal.club/meet/cherishma-reddy/share-image"
---

# Cherishma Reddy V\. on Tal

## Headline

Data Scientist & Analyst \| SQL · Power BI · Python · Machine Learning \| M\.S\. Data Science, UNCW \| Open to Work

## About

Data Scientist and Analyst with an M\.S\. in Data Science from UNC Wilmington \(Dec 2025\) and hands\-on experience building SQL pipelines, Power BI dashboards, machine learning models, and AI\-powered multi\-agent systems in real\-world business environments\. At MegaCorp Logistics, I built 3 Power BI dashboards tracking 15\+ KPIs for 10\+ stakeholders, automated ETL workflows that cut manual reporting time by 40%, resolved 500\+ data discrepancies across reporting systems, and led development of a CrewAI multi\-agent freight rate prediction pipeline integrated with Azure SQL and FastAPI, a project that combined LLM\-based query parsing, MCP tool orchestration, and real\-time pricing analytics\. My project portfolio spans healthcare fraud detection \(77% F1\-score on Medicare claims data using Random Forest \+ XGBoost\), crop yield classification \(92\.8% accuracy\), time\-series tourism demand forecasting with ARIMA/ETS, wind turbine power prediction, and a GPT\-powered fertilizer recommendation system with Streamlit and LLM explainability\. I also bring teaching experience; I served as a Graduate Teaching Assistant supporting Statistics and Data Science coursework at UNCW, and previously taught high school students in India for a year, developing strong skills in breaking down complex technical concepts for diverse audiences\. What drives me: I don't just build reports\. I help teams understand what their data is actually telling them and use it to make faster, more confident decisions\. Whether the domain is healthcare, logistics, or education, I bring the same combination of technical depth and clear communication\. Currently seeking: Data Scientist \| Data Analyst \| Teaching Instructor in Data Science or Analytics Open to: Full\-time \| Contract \| Onsite \| Remote \| Hybrid

## Location

Justin

## Work experience

Data Scientist at The Yiddish Arts and Academics Association of North America \(YAAANA\), Mar 2026 \- Present · 4 mos, California, United States, In this role, I lead statistical analysis, A/B testing, and data pipeline development to support organizational decision\-making and campaign strategy\. I validated CTA\-driven engagement variance from 1% to 13% using Python\-based A/B testing frameworks built with SciPy and Statsmodels, applying two\-sample t\-tests and chi\-square tests to ensure statistical rigor\. I conducted in\-depth EDA across 23 campaigns covering 48K\+ data points, surfacing performance trends that exceeded industry benchmarks by 6 to 12%\. On the engineering side, I built and automated ETL pipelines in Python and Azure to extract, transform, and deduplicate records loaded into Azure SQL, reducing preprocessing overhead by 50%\. I performed time\-series trend analysis using Statsmodels and Pandas on 6 months of longitudinal campaign data, producing insights that drove a permanent shift in organizational outreach strategy\. I also designed and deployed Power BI and Tableau dashboards with custom DAX measures to communicate KPIs and campaign performance to non\-technical leadership in real time\. This role sits at the intersection of statistical experimentation, data engineering, and stakeholder communication — requiring both technical precision and the ability to translate complex findings into clear, actionable recommendations for a non\-data audience\.

Data Science Practicum Intern at MegaCorp Logistics, May 2025 \- Dec 2025 · 8 mos, Wilmington, NC, I worked embedded within a logistics data team, contributing to production ML/AI systems, data engineering pipelines, and advanced analytics initiatives\. I deployed and monitored multi\-agent AI systems built on CrewAI and Python, maintaining pipeline reliability in a live operational environment\. I engineered a custom data server using Python, pyodbc, and SQLAlchemy that enabled direct, parameterized querying of live Azure SQL shipment records, forming the retrieval backbone of a larger agentic system\. I conducted time\-series feature engineering on 13 months of operational shipment data, identifying seasonal patterns and lane\-level trends that directly informed management decisions\. I optimized SQL queries and automated ETL workflows processing 3,000\+ weekly records, reducing manual reporting overhead by 40% and enabling same\-day data delivery\. The most technically complex contribution was architecting a 5\-agent freight rate prediction system using CrewAI, integrating a custom MCP tool server, LLM\-based natural\-language query parsing, a pricing calculator agent, and a FastAPI REST endpoint replacing manual freight analysis workflows and enabling stakeholders to retrieve cost\-per\-mile summaries through plain\-English queries against live Azure SQL data

Data Science Practicum Student at MegaCorp Logistics, May 2025 \- Dec 2025 · 8 mos, Agentic AI/Multi\-Agent Systems, ETL/ELT Pipelines & Data Engineering, SQL & Cloud Data\. I worked embedded within a logistics data team, contributing to production ML/AI systems, data engineering pipelines, and advanced analytics initiatives\. I deployed and monitored multi\-agent AI systems built on CrewAI and Python, maintaining pipeline reliability in a live operational environment\. I engineered a custom data server using Python, pyodbc, and SQLAlchemy that enabled direct, parameterized querying of live Azure SQL shipment records, forming the retrieval backbone of a larger agentic system\. I conducted time\-series feature engineering on 13 months of operational shipment data, identifying seasonal patterns and lane\-level trends that directly informed management decisions\. I optimized SQL queries and automated ETL workflows processing 3,000\+ weekly records, reducing manual reporting overhead by 40% and enabling same\-day data delivery\. The most technically complex contribution was architecting a 5\-agent freight rate prediction system using CrewAI, integrating a custom MCP tool server, LLM\-based natural\-language query parsing, a pricing calculator agent, and a FastAPI REST endpoint replacing manual freight analysis workflows and enabling stakeholders to retrieve cost\-per\-mile summaries through plain\-English queries against live Azure SQL data

Graduate Teaching Assistant at University of North Carolina Wilmington, Aug 2024 \- Dec 2025 · 1 yr 5 mos, Wilmington, North Carolina, United States, As a Graduate Teaching Assistant at UNC Wilmington, I supported Statistics and Data Science coursework by facilitating Python and R lab sessions, holding office hours, and developing annotated code notebooks and worked examples\. My focus was always bridging theory and practice, helping students understand not just how to execute a technique but why it matters\. Teaching demands precision: when a student asks why Random Forest outperforms a decision tree, a vague answer is not acceptable\. This crucible of explaining and adapting made me a sharper data scientist and communicator\. I actively seek roles where teaching and mentoring are valued, such as an Instructor, team lead, or in any environment that treats knowledge transfer as a core professional skill\.

Data Scientist at SystemITICS, Aug 2022 \- Jul 2024 · 2 yrs, Hyderabad, I focused on data pipeline automation, SQL optimization, and data quality initiatives supporting business intelligence and operational reporting across multiple internal teams\. I designed and automated 4 end\-to\-end Python data pipelines that reduced processing time by 30% and eliminated manual data entry errors across two business units\. I refactored legacy SQL queries using indexed CTEs and query plan optimization techniques, cutting average execution time by 40% and significantly improving reporting reliability for downstream consumers\. I monitored and troubleshot production pipelines on an ongoing basis, maintaining zero unplanned downtime over a continuous 6\-month period\. Beyond pipeline work, I applied Python and SQL to extract, clean, and analyze structured operational datasets to support business intelligence decisions\. I conducted exploratory data analysis to identify patterns and anomalies in data, built automated reporting outputs that reduced manual processing overhead, and implemented data validation frameworks to ensure accuracy and consistency across integrated systems\. I translated analytical findings into clear recommendations for product and business stakeholders, developing the ability to communicate technical results to non\-technical audiences a skill that has remained central to every data role I have held since\.

Mathematics & CS Tutor at Government Higher Secondary School \- India, Jun 2021 \- Dec 2023 · 2 yrs 7 mos, Hyderabad, Telangana, India, Provided individualized tutoring in mathematics, Python, and computer science fundamentals for high school students with diverse learning needs\. Planned lessons based on student skill levels, explained complex topics in simple ways, and offered structured practice to improve understanding and confidence\. Helped students strengthen problem\-solving abilities, prepare for exams, and improve academic performance through consistent one\-on\-one guidance\. This experience developed strong mentoring, communication, and instructional skills while demonstrating patience and adaptability in teaching\.

## Education

Master of Science \- MS, Data Science & AI, University of North Carolina Wilmington

Bachelor of Science \- BS, Mathematics Statistics and Computer Science, St\. Joseph's Degree & PG College

[View the original profile](https://tal.club/meet/cherishma-reddy)

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