Data Analyst

EDUCATION Master of Science in Information Systems, Northeastern University August 2021 - May 2023 Relevant Coursework: Algorithms, Data Science, Big Data Systems and Indexing Techniques, Machine Learning in FinTech. Bachelor of Engineering in Electronics Engineering, University of Mumbai August 2016 - October 2020 Relevant Coursework: Statistics, Object Oriented Programming, Data Structures, Data Mining, Cloud Computing SKILLS Programming Languages: Python, SQL, Java, R, JavaScript, Matlab, C++, VBA Databases: MySQL, Oracle, NoSQL, Snowflake, Mongodb, PostgreSQL, SQL Server Libraries: NumPy, Sklearn, pandas, matplotlib, seaborn, Keras, Scrapy, TensorFlow, PySpark, Pytorch Analytical / Visualization Tools: Tableau, Power BI, Looker, SAS, SPSS, RapidMiner, R-Studio, Jupyter Notebook Data Engineering: Hadoop, Spark, Kafka, Hive, Pig, Oozie, Hudi, MapReduce, BigQuery, Databricks AWS Applications: S3, EC2, SageMaker, Lambda, Redshift, Glue, QuickSight, EMR, Athena ML Algorithms: Decision Tree, Random Forest, XG Boost, Naïve Bayes, Regression, Clustering, NLP, CNN, RNN, Time Series Certifications: IBM Data Science Professional Certification EXPERIENCE KushManda.ai, United States, Remote August 2023 – Present Data Scientist - AI (Technologies: NLP, ML, Golang, Neural Networks, Generative AI, SPSS) • Built a user-based recommendation application using ML models, increasing user engagement, and achieving 10K+ views. • Worked on a Generative AI model, using LLMs, GANs and transformers for creative content generation. • Accomplished dimensionality by 22% using PCA, enhancing efficiency while preserving critical features. • Conducted time series analysis using SPSS, forecasting trends in historical data with a predictive accuracy exceeding 85%. • Integrated NLU techniques to enable the chatbot, providing personalized recommendations, increasing user satisfaction. Career Soft Solutions Inc., Edison, NJ June 2022 - August 2022 Data Engineer (Technologies: SQL, Tableau, SSIS, Python, Advanced analytics, Data Cleaning, Redshift, S3, Agile, Cloud) • Implemented Random Forest and Logistic Regression, predicting customer churn, achieving AUC score of 0.84. • Analyzed complex SQL queries to identify opportunities for optimization, resulting in 20% increase in speed and efficiency. • Developed scalable ETL processes from various sources using SSIS and Python scripting for cross-functional data extraction. • Designed business reports using Tableau, providing executive dashboards on KPIs such as revenue growth rate, customer acquisition cost, sales volume, gross profit margins etc., helping management in decision-making. • Collaborated with cross-functional teams and communicated with clients, understanding business needs and strategy. • Oversaw data migration from Oracle to Redshift using AWS DMS and S3, resulting in 10% cost savings. Atos Syntel, Mumbai, Maharashtra January 2021 - April 2021 Data Analyst Intern (Technologies: Data Warehousing, Azure ML, Databricks, Power BI, Statistical Modeling, Excel, Agile) • Designed a loan default prediction system with Regression, Random Forest, Gradient Boosting, yielding over 90% accuracy. • Spearheaded data wrangling on 1.5 million customer records, improving utilization of data warehouse for granular reporting. • Recognized patterns & built predictive models utilizing Random Forest & Power BI Dashboard to analyze complex data, which helped in analysis showing that aesthetically pleasing products have higher sales. • Performed extensive hypothesis testing, data wrangling, variable engineering, trend identification and removal. • Conducted comprehensive analysis on negative feedback of employees, leading to 15% improvement in productivity. PROJECTS Stock Market Sentiment and Time-series Analysis (Technologies: Python, ML, LSTM, Deep Learning, Flask) • Optimized the stock selection process by predicting the stock prices using the LSTM modeling technique and visualized the trends of the predicted and the actual stock prices on a web app using Flask. Spotify Music Recommendation System (Technologies: Python, Machine Learning, Unsupervised learning, NLP, Flask) • Developed a content-based filtering recommendation system, utilizing the Spotify API, comprising over 75000 distinct tracks, and utilized Flask to visualize the recommendations. • Utilized TF-IDF Vectorizer and cosine similarity to assess song similarities and enhance playlist organization. Hotel Booking Cancellation Prediction (Technologies: Python, ML, Neural Networks, Tensorflow) • Constructed multiple classification models using Random Forest, Decision Tree, Extra Tree Classifier, and Gradient Boosting with over 20 feature importance analyses, predicting hotel booking cancellations, with AUC score 0.88. Business Meeting Summarization (GCP Cloud Function, Firebase, FastAPI, Apache Airflow, Google BigQuery) • Orchestrated ETL pipelines and automated video suggestions using Airflow, established API Endpoints using FastAPI. • Deployed model as a service, joined databases with SQL, visualized results in BigQuery.