Empowering Data-Driven Decisions
Enterprise Data Solutions Expert with 4+ years of experience in leveraging data-driven insights to optimize processes and drive business growth. Specialized in transforming data into actionable insights through innovative solutions, driving efficiency and strategic decision-making.
About Me
With over 4 years of experience in enterprise analytics and machine learning, I specialize in transforming data into actionable insights. My mission is to solve complex problems through innovative, data-driven solutions, driving efficiency and strategic decision-making.
Data Engineering & Process Optimization
Skilled in building and maintaining ETL pipelines to reduce reporting cycles and improve data accuracy.
Advanced Analytics & Visualization
I design interactive dashboards and predictive models that empower cross-functional teams with real-time insights.
Leadership & Collaboration
I foster a data-driven culture while ensuring seamless integration of analytics solutions into organizational processes.
Problem-Solving
My approach includes developing scalable solutions like fraud detection systems and adaptive ML pipelines.
Education
MS in Data Science - Saint Peter's University, USA (GPA: 3.9/4.0)
BE in Computer Science - AVIT, India (GPA: 3.7/4.0)
Technical Expertise
Programming & Development
Languages
Python Libraries
Machine Learning & AI
Core ML
Deep Learning
Advanced Techniques
ML Operations
Data Engineering & Cloud
Cloud Platforms
Big Data Tools
Data Pipeline Tools
Development Tools
Data Visualization
BI Tools
Libraries
Databases
SQL
NoSQL
Business & Project Management
Methodologies
Tools
Professional Work Experience
Clinical Data Analytics Coordinator
Ocugen | Houston | July 2025 - Present
Enterprise Data Solutions Analyst
NAVCO Industries Pvt Ltd | Remote | February 2024 - Present
- Designed and deployed enterprise data solutions, improving operational efficiency by 15% and reducing reporting cycles by 30%.
- Engineered and maintained 10+ ETL pipelines using AWS Lambda and Python, cutting data processing time by 40%.
- Automated 20 reporting workflows and developed 12 dynamic dashboards in Tableau and Power BI, enhancing accessibility and reducing manual effort by 35%.
- Conducted 50+ test cases and implemented data validation workflows, increasing data accuracy by 25%.
- Mentored 6 junior analysts, fostering a data-driven culture and boosting team capacity by 20%.
Data Analyst
NAVCO Industries Pvt Ltd | March 2022 – May 2023
- Analyzed large datasets to identify trends, improving operational efficiency by 20%.
- Designed and maintained SQL databases to support data analysis and reporting.
- Presented findings to stakeholders, facilitating data-driven decision-making.
Junior Data Analyst
NAVCO Industries Pvt Ltd | October 2021 – February 2022
- Performed exploratory data analysis in Python and SQL to uncover insightful trends, patterns and correlations.
- Created interactive Tableau dashboards to visualize key metrics, elevating stakeholder data literacy.
- Employed statistical modeling and forecasting techniques to better predict future outcomes.
Junior Data Analyst
VLHS Pvt Ltd | October 2020 – August 2021
- Conducted comprehensive data analysis to support business decisions in the manufacturing and distribution of medical-grade gloves.
- Utilized statistical techniques to evaluate production processes, resulting in a 10% increase in operational efficiency.
- Created visualizations and dashboards using tools like Tableau, Power BI to report on sales trends, leading to enhanced inventory management and a reduction in overstock by 15%.
Data Analyst Intern
VLHS Pvt Ltd | August 2020 – September 2020
- Automated quality assurance workflows with Python, ensuring regulatory compliance and improving data accuracy.
- Delivered weekly and monthly analytical reports for senior leadership, supporting strategic decisions.
Volunteer Work Experience
Research Assistant
Saint Peter's University | November 2024 - Present
- Assist faculty researchers with comprehensive data collection, cleaning, and preprocessing for multiple healthcare analytics projects.
- Apply advanced statistical analysis and machine learning techniques to research data, improving predictive accuracy of clinical outcome models.
- Create data visualizations and detailed summary reports that effectively communicate complex research findings to diverse audiences.
- Collaborate with interdisciplinary research teams on literature reviews and manuscript preparation for peer-reviewed publications.
Computer Programming and Mathematics Instructor
Welugu | December 2024 - Present
- Develop and deliver comprehensive curriculum for Python, R, Java, JavaScript, HTML/CSS, and computer science fundamentals to diverse student groups.
- Design engaging assignments and assessments that effectively evaluate student progress while reinforcing practical programming skills.
- Teach advanced mathematics topics including calculus, linear algebra, discrete mathematics, and statistics with real-world applications.
- Provide personalized one-on-one tutoring sessions for students requiring additional support, resulting in improved concept mastery and confidence.
- Mentor students on independent coding projects and prepare them for programming competitions by creating interactive learning materials.
Treasurer
Saint Peter's University Data Science Club | September 2024 - April 2025
- Oversee budget allocation for data science workshops, events, and competitions while tracking all club expenses with accurate financial documentation.
- Collaborate with club leadership to develop financially sustainable activities and events that maximize value for members.
- Manage membership dues collection and process funding applications to support ongoing club initiatives.
- Present periodic financial updates during club meetings and help secure external resources and sponsorships for technical events.
Treasurer
Aarupadai Veedu Institute of Technology | July 2020 - September 2022
- Managed a ₹50,000 annual budget for student organization activities while maintaining complete financial transparency and ensuring compliance with institutional policies.
- Developed and implemented a digital tracking system that improved expense documentation efficiency by 30% and streamlined record-keeping processes.
- Prepared quarterly financial reports and presentations for organization leadership and faculty advisors, facilitating informed decision-making.
- Coordinated 5 successful fundraising initiatives that increased available funds by 25% year-over-year, enabling expanded technical workshops and competitive events.
Featured Projects
Data Professionals Insights Dashboard
Career Analytics for Data Industry Professionals
Key Achievements
- Created comprehensive dashboards analyzing demographics and career paths
- Developed insights into work-life balance and job satisfaction metrics
- Visualized programming language preferences across age groups
Technologies
Key Metrics
Skills Demonstrated
Air Quality Analytics Dashboard
Environmental Data Visualization and Analysis
Key Achievements
- Built comprehensive air quality monitoring dashboards
- Implemented pollutant correlation analysis tools
- Created seasonal trend analysis and temporal pattern recognition
Technologies
Key Insights
Skills Demonstrated
Supermarket Sales Analytics Dashboard
Retail Performance and Customer Behavior Analytics
Key Achievements
- Analyzed 1,000+ transactions to identify sales patterns
- Created customer segmentation and product affinity analysis
- Developed geographic performance visualization tools
Technologies
Key Metrics
Skills Demonstrated
Sales & Inventory Analytics Dashboard
Transforming Raw Data into Actionable Business Insights
Key Achievements
- Developed comprehensive Power BI dashboards for real-time monitoring
- Reduced inventory overstock by 15% through data-driven optimization
- Automated weekly and monthly reporting, saving 10+ hours per week
Technologies
Key Metrics
Skills Demonstrated
Dynamic Fraud Detection System
Adaptive Machine Learning for Financial Security
Key Achievements
- Built end-to-end fraud detection system with 95% accuracy
- Implemented concept drift detection for model adaptation
- Developed real-time scoring system for 1000+ transactions/second
Technologies
Key Metrics
Skills Demonstrated
Jane Street Real-Time Market Data Forecasting
Production-Grade ML for Algorithmic Trading on 47M Data Points
Key Achievements
- Developed LightGBM trading model achieving 0.014 weighted R² and 54% directional accuracy across 47M+ market opportunities
- Discovered time interaction patterns - feature_06 × time_id became top predictor, driving 29% validation R² improvement
- Engineered 48 features from 79 base features: statistical aggregates, polynomial terms, cyclical encodings, and cross-interactions
- Designed temporal validation split (80/20 by date) preventing look-ahead bias across 1,700 trading days
Technologies
Key Metrics
Skills Demonstrated
Daegu Real Estate Market Analysis
Power BI Analytics for Real Estate Investment Opportunities
Key Achievements
- Analyzed over 5,871 properties to identify investment opportunities
- Built interactive dashboards for investment and location analysis
- Developed accessibility metrics to evaluate property locations
Technologies
Key Metrics
Skills Demonstrated
Enterprise Data Lake Implementation
Scalable Data Architecture for Analytics
Key Achievements
- Designed data lake handling 5TB+ of daily data
- Created automated ETL pipelines reducing processing time by 40%
- Implemented comprehensive data quality framework
Technologies
Key Metrics
Skills Demonstrated
Template-Based RNA 3D Structure Prediction
Stanford RNA 3D Folding Competition
Key Achievements
- Achieved 0.855 mean TM-score (V3) with 100% success rate on 12 test sequences (30-720 nucleotides)
- Developed novel smart thresholding at 99.9% identity - single templates outperform ensembles for perfect matches
- Built O(n) K-mer indexing across 3,156 PDB structures for instant template lookup
- Created 5 diverse prediction strategies: single best, top-3/5/7 ensembles, quality-weighted diverse
Technologies
Key Metrics
Skills Demonstrated
AI Sustainability Risk Intelligence System
AI-Powered Insights for Business Sustainability
Key Achievements
- Developed interactive dashboards for real-time sustainability risk monitoring
- Created sector-specific risk analysis tools with custom metrics
- Implemented advanced sentiment analysis for news and public perception
Technologies
Skills Demonstrated
Interactive Keyword-Based News Retrieval
Enhancing Content Discovery with NLP and Real-Time Data Processing
Key Achievements
- Developed interactive word cloud dashboard for real-time news trend visualization
- Integrated multiple APIs (NYT, Bing News) for comprehensive content coverage
- Implemented advanced NLP techniques for keyword extraction and relevance scoring
- Created multimedia integration system combining text articles with video content
Technologies
Key Metrics
Skills Demonstrated
DoD Budget Analysis Dashboard
Interactive Analytics for Defense Budget Insights
Key Achievements
- Built interactive visualizations for complex budget data
- Developed statistical analyses for trend identification
- Created anomaly detection system for budget irregularities
Technologies
Skills Demonstrated
Forex Analysis and Prediction App
Advanced Analysis for Foreign Exchange Markets
Key Achievements
- Created real-time forex data visualization tools
- Implemented ARIMA modeling for short-term price predictions
- Developed risk management tools with custom alerts
Technologies
Skills Demonstrated
Enhancing Clinical Decision Support Systems using MIMIC Data
Developing Robust Predictive Models for Risk Assessment and Treatment Recommendations
Key Achievements
- Developed mortality prediction model with 90% accuracy and 0.784 ROC AUC score
- Achieved 100% accuracy for readmission risk prediction
- Created length of stay model with 90% accuracy and 0.967 ROC AUC
- Integrated social determinants of health into predictive models
Technologies
Data Sources
Project Scope
Adventure Works Sales Analytics Dashboard
Comprehensive Sales Performance and Customer Behavior Insights
Key Achievements
- Built multi-view dashboard tracking $24.91M in revenue and $10.46M in profit
- Created dynamic visualizations for revenue trending and geographical distribution
- Implemented customer segmentation analysis for 17.4K unique customers
Technologies
Key Metrics
Skills Demonstrated
Leveraging Synthetic Medical Data for Personalized Healthcare Insights
Big Data Analytics for Healthcare Decision Support
Key Achievements
- Built big data analytics platform using Apache Spark for healthcare insights
- Developed logistic regression model with high AUC value for personalized medicine
- Created feature importance visualization for clinical interpretation
Technologies
Project Scope
Skills Demonstrated
Analysis of COVID-19 Clinical Trial Data
Data Mining and Predictive Modeling of Global Pandemic Research
Key Achievements
- Analyzed 5000+ COVID-19 trials from ClinicalTrials.gov using data mining techniques
- Developed a Linear Discriminant Analysis model with 48.9% accuracy for trial status prediction
- Created visualizations to identify patterns in trial designs and participant enrollments
- Implemented Principal Component Analysis for dimensionality reduction and pattern discovery
Technologies
Methods Used
Skills Demonstrated
Mental Health Trends and Risk Modeling
Informing Gender-sensitive Policy and Interventions through Data Analysis
Key Achievements
- Analyzed global mental health trends using Kaggle datasets from the Global Burden of Disease Collaborative Network
- Developed generalized linear models (GLM) to predict depression prevalence with 13% improved accuracy
- Uncovered relationship between GDP volatility and disproportionate increases in female depression rates
Technologies
Key Findings
Skills Demonstrated
Publications
Finance Trading Algorithms in High-Frequency Markets: Predictive Modeling, Reinforcement Learning, and Real-Time Anomaly Detection
International Journal of Computer Technology and Electronics Communication (IJCTEC)
September-October 2025 • Volume 8, Issue 5
This research develops a unified algorithmic trading system for high-frequency markets that integrates predictive modeling, reinforcement learning, and real-time anomaly detection. The framework uses calibrated machine learning models (gradient boosted trees and temporal convolutional networks) to forecast short-horizon price movements, employs CVaR-constrained reinforcement learning for inventory-aware execution, and implements streaming anomaly detectors to reduce tail risk during market stress.
Testing on limit order book data with rolling walk-forward validation showed improved risk-adjusted returns over baseline strategies while maintaining sub-450 microsecond end-to-end latency. The system demonstrated resilience during simulated flash-crash scenarios, reducing maximum drawdown from 10.5% to 6.2% in high-volatility regimes through graded anomaly responses.
Open to collaborations on extending this work to multi-venue coordination, causal feature engineering, and broader asset class validation. Seeking feedback from quantitative researchers and trading system practitioners.
Technologies:
Hybrid Deep Learning and Econometric Models for Financial Market Forecasting: A Review of Emerging Approaches and Their Impact on Trend Prediction
IRE Journals
October 2025 • Volume 9, Issue 4
Co-Author: Adarsh Pramodan Kandoth
This research provides a comprehensive review of hybrid modeling approaches that combine traditional econometric methods with deep learning techniques for financial market forecasting. The study systematically analyzes how integrating models like ARIMA and GARCH with neural architectures such as LSTM networks and CNNs can overcome the limitations of standalone methods in capturing both linear and nonlinear market dynamics.
Through comparative analysis of recent literature across stock markets, foreign exchange, and commodity prices, the review demonstrates that hybrid models consistently achieve superior predictive accuracy with lower RMSE and MAE values compared to traditional econometric or pure deep learning approaches. The research identifies three primary integration strategies: ARIMA combined with recurrent networks for temporal dependencies, GARCH merged with convolutional architectures for volatility modeling, and stochastic volatility models enhanced with deep learning for capturing market uncertainty.
Key findings reveal that while hybrid models significantly improve forecast precision and robustness across diverse financial instruments, critical challenges remain in model interpretability, causal inference, computational complexity, and effective integration of domain knowledge. The study highlights research gaps in explainable AI for financial forecasting, handling endogeneity in market data, and generalization across different market regimes and asset classes.
Technologies:
