About Me
Bridging data science and creative development
Hello There!
I'm a tech-driven problem solver with a knack for uncovering insights hidden in data and transforming them into actionable outcomes. My passion for technology, coding, and design fuels my enthusiasm for tackling real-world challenges through innovative solutions.
My background as an Analytics Engineer and Machine Learning Enthusiast involves building data pipelines, developing predictive models, and integrating diverse data sources to create impactful strategies. I enjoy automating workflows, interpreting complex data, and delivering insights that enable informed decision-making.
Collaboration and mentorship are key to my professional journey, as I believe shared knowledge and teamwork drive the best outcomes. Outside of work, you'll find me on the cricket field—where I've learned valuable lessons in strategy, adaptability, and perseverance, which I apply in both my professional and personal life.
Let's connect to explore how my skills and passion can help solve your most pressing challenges. Together, we can turn ideas into results! I'm located in the United States and always excited to collaborate on innovative projects.
Technologies & Skills
My Work
Here are some of the projects I've worked on that showcase my skills in data analysis, machine learning, and full-stack development.
Web Scraping & Analysis for Crime News
Performed web scraping for crime-related news headlines and post dates in New York, applied sentiment analysis for scoring, and generated a time-series plot to illustrate average sentiment scores over dates, offering insights into evolving news sentiments.
Recommendation System
This movie recommendation system, built using KNN, Slope One, and SVD algorithms, offers personalized and accurate movie recommendations to users. Developed in Python, it uses large datasets and various metrics for evaluation. The project includes a web interface for users and documentation for easy setup and contributions.
Online Auction Platform
The Online Auction website is developed using JavaScript, Java, SQL Workbench, and Tomcat Server. It offers a user-friendly interface with features like bidding, item listing, user authentication, and payment processing. The project includes a documented database schema and scripts, enabling easy setup and contributions by developers.
COVID-19 Analysis
Developed an informative dashboard to view the overall number of persons affected, recovered, and died by the devastating COVID-19 virus in a Demographic and Gender Level, as well as perform time-series analysis on this data.
Diabetes Prediction
Created a model to predict diabetes in patients based on parameters such as pregnancy, glucose, blood pressure, body mass index (BMI), age, and so on. 80% accuracy was projected using algorithms such as Logistic Regression, Naive Bayes, Random Forest, and SVC.
Car Price Prediction
The main objective of this research is to forecast the precision of a linear regression model based on the used-car sale price. Both buyers and sellers may utilize this model to make well-informed decisions about the price of a vehicle.
Image and Digit Classification
Built classifiers for identifying faces and categorizing numbers. The three classifiers were that we used are Naive Bayes, Perceptron, and K Nearest Neighbor.
Rainfall Prediction
The goal is to examine the overall quantity of rainfall in India from 1900 and 2016. I completed the pre-processing processes by cleaning, validating, analyzing, and displaying the data to gain clear and improved insights.
Maze Traversal
Maze generation is done using DFS. The BFS and A star algorithms are used to identify a path for the agent to take in order to achieve the objective state.
Wine Quality Prediction
Analyzed wine quality, predicting it based on ingredients using machine learning techniques like Logistic Regression, Naive Bayes, and Random Forest, achieving a 98% accuracy.
MediBlock WebApp
The project's goal is to use a decentralized WebApp to monitor the drugs that are supplied to consumers. HTML, CSS, JavaScript Framework, and Solidity are used to build the Web Application.
Games Corner WebApp
The main objective is to build a website for the users to play games that are built using JavaScript and the Java platform.
Web Scraping & Analysis for Crime News
Performed web scraping for crime-related news headlines and post dates in New York, applied sentiment analysis for scoring, and generated a time-series plot to illustrate average sentiment scores over dates, offering insights into evolving news sentiments.
Recommendation System
This movie recommendation system, built using KNN, Slope One, and SVD algorithms, offers personalized and accurate movie recommendations to users. Developed in Python, it uses large datasets and various metrics for evaluation. The project includes a web interface for users and documentation for easy setup and contributions.
Online Auction Platform
The Online Auction website is developed using JavaScript, Java, SQL Workbench, and Tomcat Server. It offers a user-friendly interface with features like bidding, item listing, user authentication, and payment processing. The project includes a documented database schema and scripts, enabling easy setup and contributions by developers.
COVID-19 Analysis
Developed an informative dashboard to view the overall number of persons affected, recovered, and died by the devastating COVID-19 virus in a Demographic and Gender Level, as well as perform time-series analysis on this data.
Diabetes Prediction
Created a model to predict diabetes in patients based on parameters such as pregnancy, glucose, blood pressure, body mass index (BMI), age, and so on. 80% accuracy was projected using algorithms such as Logistic Regression, Naive Bayes, Random Forest, and SVC.
Car Price Prediction
The main objective of this research is to forecast the precision of a linear regression model based on the used-car sale price. Both buyers and sellers may utilize this model to make well-informed decisions about the price of a vehicle.
Image and Digit Classification
Built classifiers for identifying faces and categorizing numbers. The three classifiers were that we used are Naive Bayes, Perceptron, and K Nearest Neighbor.
Rainfall Prediction
The goal is to examine the overall quantity of rainfall in India from 1900 and 2016. I completed the pre-processing processes by cleaning, validating, analyzing, and displaying the data to gain clear and improved insights.
Maze Traversal
Maze generation is done using DFS. The BFS and A star algorithms are used to identify a path for the agent to take in order to achieve the objective state.
Wine Quality Prediction
Analyzed wine quality, predicting it based on ingredients using machine learning techniques like Logistic Regression, Naive Bayes, and Random Forest, achieving a 98% accuracy.
MediBlock WebApp
The project's goal is to use a decentralized WebApp to monitor the drugs that are supplied to consumers. HTML, CSS, JavaScript Framework, and Solidity are used to build the Web Application.
Games Corner WebApp
The main objective is to build a website for the users to play games that are built using JavaScript and the Java platform.
Experience
My professional journey in data science, analytics, and machine learning.
Work Experience
Data Infrastructure Engineer
Workforce Professionals Training Institute
July 2024 - Current
Built predictive models integrating TalentLMS, QuestionPro, and SurveyMonkey into Snowflake, reducing data processing time by 35%. Automated workflows using AWS Lambda and Apache Airflow, improving model training efficiency and data ingestion.
Data Scientist
Rutgers Institute for Nicotine and Tobacco Studies
October 2023 - Current
Built strong data pipelines by integrating social media APIs for monitoring tobacco discussions. Used Python, SQL, TensorFlow, PyTorch, and NLP for data analysis, applying Machine Learning for content prediction. Led on-time, under-budget project delivery, exceeding goals by 30%.
Business Intelligence Analyst
Heldrich Center for Workforce Development
June 2023 - August 2023
Analyzed CTE Program data, revealing strong links between program details and job rates. Categorized data for program selection. Conducted A/B Testing to fine-tune improvements, resulting in a 5x increase in enrollment and job rates, earning recognition from the NJ Education Department. Improved workforce decisions using data insights.
Data Analyst
Vue.ai
February 2021 - August 2022
As the Head of Analytics Onboarding, my role encompasses guiding data-driven decisions and integrating 20+ clients successfully. I've driven substantial revenue growth for 40+ global retail enterprises through analytics, data analysis, and strategic guidance, resulting in impressive 5x to 10x increases. My efforts extend to enhancing team efficiency with an automated email-based reporting system, reducing workload by 50%. I've showcased my expertise in data extraction, aggregation, and ETL, facilitating scalable data pipelines. Additionally, I've implemented automated verification and reconciliation systems, improving data accuracy, and conducted A/B testing for recommendation engines.
Machine Learning & Analytics Engineer
Dapplogix Software Private Limited
January 2020 - October 2020
Designed a sentiment analysis model for social media activity classification. Utilized Selenium, NLP techniques, and LSTM networks for an impressive 94% accuracy rate in processing sequential data.
Education
Master's in Computer Science
Rutgers, The State University of New Jersey
Bachelor's in Computer Science & Engineering
Anna University
High School
DAV Matriculation Higher Secondary School
Services
Comprehensive solutions tailored to transform your data and digital presence.
Data Analytics
Transform raw data into actionable insights with advanced analytics, statistical modeling, and predictive analysis to drive informed business decisions.
Data Integration
Seamlessly connect and unify multiple data sources, APIs, and databases to create a comprehensive, real-time view of your business operations.
Machine Learning
Develop intelligent systems and algorithms that learn from data to automate processes, predict outcomes, and optimize performance.
Interactive Dashboards
Create stunning, interactive visualizations and dashboards that make complex data accessible and actionable for stakeholders at all levels.
Full-Stack Development
Build robust, scalable web applications from concept to deployment, ensuring optimal performance and user experience across all devices.
Creative Design
Craft visually striking and effective designs that communicate your message clearly and create memorable brand experiences.
Tableau Dashboards
Interactive data visualizations and dashboards created with Tableau for data-driven insights and decision making.
NYC Crime Insights Visualization
Interactive visualization of crime patterns and trends in New York City with demographic analysis and geographic mapping.
Climate Trends: Temperature Changes Visualization
Comprehensive analysis of global climate patterns and temperature changes over time with interactive filters and trend analysis.
COVID-19 Analysis: Time Series Visualization
Real-time COVID-19 data visualization with demographic breakdowns, time series analysis, and geographic impact mapping.
Urban Pulse: NYC Hosts & Neighborhoods Visualization
Analysis of New York City neighborhoods and hosting patterns with interactive maps and demographic insights.
San Diego Stays: Accommodations & Bookings Visualization
Comprehensive analysis of San Diego accommodation patterns and booking trends with seasonal analysis and pricing insights.
Global COVID-19 Impact: Geographic Visualization
Worldwide COVID-19 impact analysis with country-level data, infection rates, and recovery statistics visualization.
NYC Crime Insights Visualization
Interactive visualization of crime patterns and trends in New York City with demographic analysis and geographic mapping.
Climate Trends: Temperature Changes Visualization
Comprehensive analysis of global climate patterns and temperature changes over time with interactive filters and trend analysis.
COVID-19 Analysis: Time Series Visualization
Real-time COVID-19 data visualization with demographic breakdowns, time series analysis, and geographic impact mapping.
Urban Pulse: NYC Hosts & Neighborhoods Visualization
Analysis of New York City neighborhoods and hosting patterns with interactive maps and demographic insights.
San Diego Stays: Accommodations & Bookings Visualization
Comprehensive analysis of San Diego accommodation patterns and booking trends with seasonal analysis and pricing insights.
Global COVID-19 Impact: Geographic Visualization
Worldwide COVID-19 impact analysis with country-level data, infection rates, and recovery statistics visualization.
Get In Touch
Ready to start a conversation? Let's discuss how we can work together to achieve your goals.
© 2024 Darshan Senthil. All rights reserved.