Prajwal Venkat V — Business Analyst

Data Analyst | Business Analyst | Risk & BI I turn complex data into strategic decisions that move key performance indicators (KPIs). With a track record of delivering $1.6M in annual fraud savings on over 3M transactions, I specialize in uncovering patterns and building solutions that directly impact the bottom line. My work has consistently cut false positives by 18% and saved teams 15 hours per week through automated dashboards and streamlined processes. I'm a data analyst who starts with the business problem. I partner with stakeholders to define requirements and translate their questions into actionable, SQL-first analysis, hypothesis testing/AB testing, and forecasting models. I then deliver these insights in Power BI and Python so they are audit-ready and easy to act on. I currently work as a Research Assistant at The University of Texas at Arlington further refining my skills in federated machine learning. I recently completed my Master's in Data Science from UT Arlington (GPA 4.0), where I focused on machine learning and building systems that solve real-world problems. As a Graduate Teaching Assistant, I guided over 100 students through hands-on labs in Python, SQL, and Power BI, which sharpened my ability to explain complex ideas clearly, a skill I bring to every team. My experience at Valley Infosystems as a Data Scientist highlights my ability to drive results. I built fraud detection tools and automated data pipelines, creating dashboards with SHAP explainability to align model insights with stakeholder needs. Our work led to three key wins: it achieved $1.6M+ in annual fraud savings, cut review time by 13%, and improved case escalation efficiency, resulting in faster, smarter decisions across the team. Skills & Tools: SQL (CTEs, window functions), Power BI (DAX, Power Query), Excel, Tableau, Python (pandas, scikit-learn), ETL/ELT, data modeling, KPI dashboards, forecasting, hypothesis testing/A-B, stakeholder management, requirements gathering, risk/fraud analytics, SHAP, Streamlit. Open to: Business Analyst, Data Analyst, BI Analyst, and Risk Analyst roles where I can help teams move faster, think clearly, and make smarter decisions backed by data.

Stackforce AI infers this person is a Data Science and Analytics professional with a focus on Fintech and Education sectors.

Location: Arlington, Texas, United States

Experience: 2 yrs 5 mos

Skills

Data Analysis
Business Analysis
Data Visualization
Teaching
Data Science
Risk Analytics
Data Engineering
Machine Learning

Career Highlights

Delivered $1.6M in annual fraud savings.
Cut false positives by 18% in fraud detection.
Improved student assessment outcomes by 40%.

Work Experience

The University of Texas at Arlington

Research Analyst (11 mos)

Data Analyst | Graduate Teaching Assistant (11 mos)

VALLEY INFOSYSTEMS PRIVATE LIMITED

Data Scientist (7 mos)

Suvidha Foundation (Suvidha Mahila Mandal)

Machine Learning Intern (1 mo)

Verzeo

Machine Learning Intern (1 mo)

Education

Master of Science - MS at The University of Texas at Arlington

Bachelor of Engineering - BE at Ramaiah Institute Of Technology

Prajwal Venkat V

Business Analyst

Arlington, Texas, United States2 yrs 5 mos experience

Most Likely To Switch

Key Highlights

Delivered $1.6M in annual fraud savings.
Cut false positives by 18% in fraud detection.
Improved student assessment outcomes by 40%.

Stackforce AI infers this person is a Data Science and Analytics professional with a focus on Fintech and Education sectors.

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Skills

Core Skills

Data AnalysisBusiness AnalysisData VisualizationTeachingData ScienceRisk AnalyticsData EngineeringMachine Learning

Other Skills

A/B TestingAgile MethodologiesAnalytical SkillsAnalyticsAutonomous DatabaseBig Data AnalyticsBusiness Impact AnalysisCNNsCloud Security FundamentalsCommunicationCompartments & TaggingComplianceCost Management & Budget AnalysisCross-team CollaborationData Analytics

About

Experience

2 yrs 5 mos

Total Experience

1 yr 2 mos

Average Tenure

1 yr 10 mos

Current Experience

The university of texas at arlington

2 roles

Research Analyst

Jul 2025 – Present · 11 mos · Arlington, Texas, United States

Data Analyst | Graduate Teaching Assistant

Aug 2024 – Jul 2025 · 11 mos · Arlington, Texas, United States

Data Analyst | Graduate Teaching Assistant
As a GTA for Data Science (DASC 5301) and Machine Learning (DASC 5304), I operated as a Data analyst for the program, gathering stakeholder requirements, analyzing student records with SQL/Excel, and building Tableau KPI dashboards to deliver validated, actionable insights; I also documented methods and presented findings to non-technical stakeholders.
Analyzed student records with SQL and Excel to surface trends and bottlenecks, leading to 20% process efficiency in academic workflows.
Built real-time Tableau KPI dashboards (attendance, assessments, interventions) that enabled self-serve insights and lifted engagement by 25%, co-designing metrics with faculty and advisors.
Captured and documented stakeholder requirements and translated business needs into technical solutions from metric definitions to dashboard wireframes.
Designed and delivered 12+ hands-on workshops (SQL, analytics, BI) for 80+ participants, to target skills gaps and contributing to a 40% improvement in assessment outcomes.
Led ML lab sessions (Python/scikit-learn) on EDA, feature engineering, cross-validation, and model evaluation; prevented data/target leakage and improved experiment rigor.
Provided 1:1 support to debug SQL/Python and refine project logic, reinforcing data quality, validation, and reproducible workflows.

SQLExcelTableauData AnalysisBusiness Analysis

Valley infosystems private limited

Data Scientist

Oct 2022 – May 2023 · 7 mos

Deployed an anomaly detection model for a banking client with the risk team, handling over 3+ million card-not-present transactions.
Boosted AUC-ROC from 0.81 to 0.89 and reduced false positives by 18%, leading to a projected $1.6 million in annual savings.
Automated data validation and feature engineering using Python, Pandas, and Scikit-learn, improving reproducibility and cutting QA review time by 30%.
Built SHAP-enhanced dashboards in Power BI to surface model insights, which improved fraud triage speed by 13% and helped teams escalate cases faster.
Worked with risk and business stakeholders to integrate model outputs into daily fraud decision-making workflows.

PythonPandasScikit-learnPower BIData ScienceRisk Analytics

Suvidha foundation (suvidha mahila mandal)

Machine Learning Intern

Oct 2021 – Nov 2021 · 1 mo · Remote

Collaborated with a 4-person development team to sort/ clean/ categorize and class-balance on 42,000+ botanical images within a 1-month sprint.
Developed and trained CNNs in TensorFlow (MobileNetV2, VGG16) with robust pipelines (train/val splits, early stopping, data augmentation).
Reached 80.9% validation accuracy, a +39% lift vs. initial baseline (58% → 80.9%) Random forest model.
Applied Grad-CAM to validate model attention on salient botanical structures, improving stakeholder confidence and model explainability.
Benchmarked deep learning vs. classic ML, documenting metric deltas and error analysis to guide model selection for production.
Optimized training throughput (batching, caching, mixed practices) to balance generalization and runtime, enabling rapid iteration and deployment readiness.

TensorFlowCNNsMachine Learning

Verzeo

Machine Learning Intern

May 2021 – Jun 2021 · 1 mo

Strengthened core ML fundamentals while applying supervised learning to real-world text and image datasets
Built sentiment analysis and digit classification models using Logistic Regression and SVM.
Improved sentiment model accuracy by 18% and reduced prediction errors by 15% through data preprocessing and tuning.
Automated text cleaning and data wrangling workflows, saving 6 hours per week in manual preprocessing.
Delivered insights and final model results through Python-based reporting tools and Jupyter Notebooks

PythonLogistic RegressionSVMMachine Learning