Venkata Panem

Lead Data Scientist | Machine Learning Engineer

Verizon

Jan 2025 - Current (1 year 4 months)

• Led development of intelligent transaction categorization models combining machine learning andrule based logic, improving classification accuracy by 35% and enabling automated general ledger mapping across diverse financial data sources. • Built a real-time fraud detection system using ensemble models and anomaly detection to flag suspicious activities in financial records, reducing false positives by 25%—vital for accounting compliance and audit readiness. • Automated parsing and reconciliation of bank statements via NLP, OCR (pdfplumber), and document intelligence—accelerating data extraction by 60% and reducing turn around time for P&L reporting, expense classification, and underwriting. • Created a deep learning pipeline (YOLO) f

Senior Data Scientist | Machine Learning Engineer

Comcast

Feb 2023 - Dec 2024 (1 year 11 months)

• Built large-scale ML models to enhance enterprise data retrieval and document intelligence, improving search ranking, query understanding, and driving a 40% increase in user engagement across workplace tools. • Developed NLP pipelines using BERT and GPT to extract structured insights from unstructured internal content—skills transferable to invoice parsing, ledger mapping, and financial narrative analysis for accounting use cases. • Led the development of personalized recommendation systems using collaborative filtering and deeplearning, enhancing content relevance and supporting future AI-based decision support features. • Partnered with data engineering teams to architect robust data ingestion and feature engineering pipelines, enab

Senior Data Engineer | ML Engineer

Presbyterian Healthcare Services

Nov 2019 - Jan 2023 (3 years 3 months)

• Developed and deployed ML models to solve complex business problems across finance, retail, andhealthcare—improving decision-making accuracy by up to 30% in high-stakes environments. • Designed predictive analytics systems using supervised and unsupervised learning to support credit risk scoring, financial forecasting, and customer segmentation for enterprise clients. • Built and optimized data preprocessing and feature engineering pipelines to handle large-scale, highdimensional datasets using Python and Spark, improving model training efficiency. • Collaborated with clients and cross-functional teams to translate evolving business needs into end-toend ML strategies, contributing to fast-turnaround, high-impact solutions—ideal for ea

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Data Scientist | Data Engineer

ROSE L. BRAND &Associates P.C

Aug 2017 - Nov 2019 (2 years 4 months)

• Automated recurring PowerBI dashboards, cutting analyst workloads significantly while delivering reports faster and more consistently across departments. • Improved BI team productivity by building an ETL automation tool that moved data from the warehouse to reporting layers, reducing manual preparation needs. • Delivered 50+ interactive reports and dashboards that provided legal and finance teams with clear visibility into KPIs, accelerating their decision cycles. • Standardized SQL queries and stored procedures, reducing onboarding time for new developers and improving the maintainability of analytics systems. • Collaborated with IT and compliance teams to integrate secure reporting solutions, ensuring data use adhered to strict le

Data Engineer

Wipro Limited

Jun 2013 - Jan 2016 (2 years 8 months)

• Improved production processes by applying anomaly detection to operational data, surfacing hidden issues that directly influenced product performance. • Enhanced reporting reliability through advanced SQL query optimization and reusable ETL frameworks, enabling faster access to critical business metrics. • Increased team productivity by mentoring colleagues in business intelligence practices, which raised consistency and accelerated on-time delivery of analytics projects. • Collaborated with operations to implement data monitoring tools, giving managers early warning signals of data quality problems in day-to-day workflows.

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