Hi there!

i am Rutika Kadam

Passionate Data Scientist & Machine Learning Engineer

Driven by the belief that “Data is a gift from yesterday that you receive today to make better tomorrow.” I'm deeply passionate about harnessing the power of data to solve real-world problems, driving my curiosity and dedication to Data Science and Artificial Intelligence.

About Me

about me

I am Rutika Avinash Kadam, a Master's in Data Science student at the State University of New York at Stony Brook, with over 4 years of professional experience in the IT industry. Throughout my career, I have honed core skills in Machine Learning, Predictive Modeling, Deep Learning, Natural Language Processing, Data Analysis, and Data Visualization and have a strong passion for Artificial Intelligence.

I am actively seeking opportunities in roles such as Data Scientist, Machine Learning Engineer, AI/ML Engineer, Data Engineer, Data Analyst, and Business Analyst—where I can contribute to building intelligent, data-driven solutions that support impactful decision-making and innovation.

My Education

  • Master of Science in Data Science, 2024 – 2026

    State University of New York at Stony Brook

  • Bachelor of Engineering in Information Technology, 2016 – 2020

    Savitribai Phule Pune University

Download CV Projects

my skills

Machine Learning
Deep Learning
Natural Language Processing
Artificial Intelligence
Data Wrangling
Predictive Modeling
Data Visualization
Extract Transform Load
Python
R
MySQL
Statistics
Azure
GIT
Microsoft Office Suite

my projects

Project 1

AskYourDocument

A Retrieval-Augmented Generation (RAG) application that enables intelligent Q&A over documents and web content using FAISS, SBERT, and Google Generative AI.

Project 2

SmartApply

A Gradio-based resume analysis app leveraging Google Gemini API to generate ATS match %, summaries, and skill insights, deployed on Hugging Face Spaces.

Project 1

ScoreCast - Academic Score Forecasting

A machine learning framework for predicting student math scores using ensemble and linear models.

Project 2

CensusIncome-Classifier

A supervised ML pipeline to classify income levels using AIC-driven feature selection and ensemble classifiers.

Project 5

ConversionFlow Analyzer

An interactive Power BI dashboard for analyzing Swiggy’s user conversion funnel and channel trends.

Project 4

AirlineDB Insights

Executed SQL-based analysis on airline data to derive KPIs like on-time rates and occupancy. Leveraged joins, window functions, and CASE logic for dynamic, 95%-accurate reporting.

my experience

Research Assistant @ Stony Brook Medicine
July 2025 - Present, Stony Brook, USA
  • Built reproducible missing data imputation pipelines in R & SAS for a prospective cohort of 10,000+ women (aged 65+) in the Study of Osteoporotic Fractures; performed exploratory analysis of missingness patterns to assess MCAR, MAR, and MNAR mechanisms.
  • Implemented Multiple Imputation by Chained Equations (MICE) along with alternative imputation strategies (mean, hot-deck, regression) to ensure robustness; evaluated convergence diagnostics, sensitivity analyses, and cross-method consistency.
  • Developed & validated machine learning models (logistic regression, other bagging and boosting algorithms) to predict physical function decline & fracture risk; applied cross-validation and hyperparameter tuning across multiple imputed datasets for reproducibility.
Systems Analyst @ Tata Consultancy Services
August 2020 - April 2024, Pune, india
  • Collaborated with the Vulnerability Management team to perform Risk Analysis on vulnerability datasets from Qualys VMDR across 55K+ Windows assets & 1M+ vulnerabilities, uncovering trends, anomalies, & threat vectors using Python & MySQL.
  • Implemented predictive models for vulnerability prioritization & patch management timelines, leveraging engineered features like CVSS-weighted risk scores & patch urgency indices, leading to a 15% reduction in security risks.
  • Developed supervised ML models (logistic regression, boosting algorithms, ANN) to predict the likelihood of exploitability using CVE metadata, asset attributes, & historical remediation data, improving prioritization efficiency by 25%.
  • Employed Data Analysis Expressions (DAX)-enhanced KPIs like CVSS score, threat intelligence, exploitability, risk levels, remediation timelines, deployment status, compliance rates within Power BI driven Vulnerability Analysis Dashboard.
  • Designed & deployed feasible technical solutions using Microsoft Endpoint Configuration Manager to remediate Windows & application vulnerabilities with 99% compliance; optimized configurations & automated tasks using PowerShell, boosting productivity by 25%.
  • Provided dependable IT support, proactively responding client queries, via ITIL framework-based processes like Incident, Change, Service Request Management using ServiceNow, working in Service Operation phase.
Data Engineer Intern @ Zensar Technologies
May 2019 - July 2019, Pune, India
  • Built ETL pipelines using Azure Data Factory to process ~30GB of transactional & web traffic data stored in Azure Data Lake Gen2; leveraged this data to perform Funnel Analysis for India’s leading e-commerce food ordering platform, Swiggy, identifying key drop-off points & reducing cart abandonment by 11%.
  • Built interactive Power BI dashboards to visualize conversion rates, traffic sources & user journey patterns; collaborated with marketing to optimize campaigns, increasing high-intent traffic by 15%.
  • Tracked pipeline enhancements & analysis results in JIRA, ensuring reproducibility & alignment with business KPIs.

contact me

My Email

rutikakadam2727@gmail.com

My Number

+1 (934) 949-8653

My Address

New York Metropolitan Area, New York, USA