About Me

Open to Work - Actively seeking Data Science, Data Analyst & ML Engineering roles

Professional Summary

I started in electrical engineering, moved into business strategy through an MBA, and found my true calling where they intersect: turning messy data into clear decisions. My path from IoT sensor data at Smart Bridge to building ML pipelines and Power BI dashboards taught me something most bootcamps skip: understanding the business question matters as much as the algorithm.

Today, I build predictive models that solve real problems - mortgage payoff prediction across 622K records, customer targeting that ranked 50K prospects into actionable deciles, COVID-19 mortality analysis that identified key risk drivers. I am completing my M.S. in Data Analytics at Webster University with hands-on experience in Azure ML, Databricks, and cloud-based model deployment.

What sets me apart: I can build the model AND explain it to the VP who needs to act on it. That is what an engineering + MBA + data science background gives you.

Core Competencies

Machine Learning & Predictive Modeling
Neural Networks (CNN, RNN, Transformers)
NLP & LLM Evaluation (BERT, RoBERTa)
Agentic AI Workflows & Generative AI
Power BI, Tableau & Data Visualization
ETL, Data Pipelines & SQL Analytics
Feature Engineering & Model Evaluation
Azure ML, Databricks & Apache Spark
Information Retrieval & Recommendation Systems
KPI Analysis & Stakeholder Reporting
Data Governance, Privacy & Security
Requirements Analysis & Cross-functional Communication

What I Have Built

622K+ Records Processed

Built ML pipeline for mortgage payoff prediction using panel loan data across 60 months

AUC 0.902 Response Model

Direct mail targeting model that ranked 50K customers into actionable response deciles

8+ Forecasting Models

Time series portfolio comparing ETS, TBATS, STL, and benchmark models across domains

M.S. Data Analytics

Webster University - advanced coursework in ML, statistics, and analytics programming

3,500+ Lines of JS

Hand-coded interactive analytics page with 14 ML demos, zero frameworks

5 Industry Domains

Applied ML across healthcare, finance, marketing, IoT, and cybersecurity

Education & Experience

Aug 2023 - May 2026

M.S. in Data Analytics

Webster University, St. Louis, MO

Coursework: Applied Business Statistics, Analytics Programming (R, Python), Databases & Warehousing, Data Visualization, Machine Learning, Time Series Analytics, Analytics Practicum

Jan 2022 - Dec 2022

Graduate Research Assistant - Industry-Oriented Research

Osmania University, Hyderabad, India (Hybrid)

  • Conducted applied research in cybersecurity and industrial safety using data cleaning, EDA, statistical modeling, and analytical reporting; identified patterns, trends, and data quality issues
  • Partnered with faculty and stakeholders to gather requirements, scope analyses, and translate business/security needs into analytical workflows
  • Produced executive summaries, process documentation, and analytical reports for risk assessment and decision-making while adhering to governance, privacy, and security requirements
  • Investigated data inconsistencies across sources, documented root causes, and implemented data quality checks to improve metric integrity
  • Assisted in developing, testing, and evaluating statistical, predictive, and ML models for security, risk, and operational decisions
  • Presented simplified, executive-ready insights for non-technical stakeholders
Jan 2021 - Feb 2022

Data Analyst - Independent Analytics Engagements

Data Analytics & Business Intelligence, Hyderabad, India (Remote)

  • Collected, cleaned, and validated sales, operations, and customer data (Excel + relational sources) for analytics readiness across thousands of records
  • Performed EDA to detect trends, anomalies, and data quality issues, improving reporting reliability and insight quality
  • Built Power BI dashboards for revenue performance, product metrics, and customer segmentation with KPI scorecards and drill-down views
  • Wrote/optimized SQL queries for extraction, transformation, KPI tracking, and recurring reporting, reducing manual analysis effort
  • Defined and monitored KPIs aligned to business objectives; ensured consistent metric definitions across reports and stakeholders
  • Reconciled dashboards with source data to validate outputs and resolve discrepancies
  • Delivered actionable insights via clear visuals and concise recommendations for non-technical stakeholders
2020 - Dec 2022

MBA in Technology Management (IT)

Osmania University, Hyderabad, India

Coursework: Business Analytics, Relational Database Management Systems, Information Systems, Risk & Process Analysis

2016 - Nov 2020

B.Tech in Electrical & Electronics Engineering

Osmania University, Hyderabad, India

Built a strong analytical foundation in engineering principles, signal processing, and embedded systems. Developed problem-solving and quantitative reasoning skills directly applicable to data science and ML.

May 2019 - Jun 2019

Data Analyst Intern (IoT / Security Systems)

Smart Bridge - IBM Collaboration, Hyderabad, India

  • Built an RFID smart access-control system in C/C++ with authorization logic, event logging, and validation for reliability and auditability
  • Generated structured event-level data to enable monitoring, anomaly detection, and operational analysis with event logs captured across repeated test runs
  • Cleaned/analyzed system logs to identify access patterns, failure modes, and abnormal behavior; used quantitative metrics where applicable
  • Performed EDA on latency, consistency, signal reliability; applied root-cause analysis to diagnose anomalies and failures
  • Documented system behavior, data flows, and validation results; produced artifacts supporting traceability, governance, and predictive monitoring

Currently Learning

Staying ahead of the curve with emerging technologies

Large Language Models (LLMs)
MLOps & Model Deployment
Transformer Architecture
Cloud Architecture (AWS)
Generative AI & Agentic Workflows
Apache Spark & Databricks

Achievements & Recognition

Best Data Science Project

Awarded for innovative solution in healthcare analytics

Published Research

Authored research paper on future trends in data analytics & AI decision systems

M.S. Data Analytics

Webster University - ML, statistics, analytics programming

5 Industry Domains

Applied data science across healthcare, finance, marketing, IoT, and cybersecurity

GitHub Activity

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Want to know more?

Download my full resume for a detailed overview of my experience, skills, and qualifications.

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