Neha N. V.

About Neha N. V.

Highly efficient Data Scientist/Data Analyst with 5+ years of experience in data analysis, machine learning, data mining, and predictive modeling. Proficient in Python, R, and big data technologies (Hadoop, Spark, PySpark) for advanced analytics, statistical modeling, and data visualization using Tableau, Power BI, and Qlik. Extensive experience in AWS (SageMaker, S3, Lambda, Redshift, Glue) and Azure (Machine Learning, Databricks, Synapse Analytics) for building, deploying, and managing scalable ML models and data pipelines. Skilled in text analytics, NLP, and advanced ML techniques like Random Forest, SVM, and neural networks for solving complex business problems. Expertise in SQL and NoSQL databases (MongoDB, Cassandra) for efficient data querying, management, and retrieval. Hands-on experience with deep learning frameworks (TensorFlow, Keras) and Scikit-learn for model development, optimization, and deployment. Proficient in designing end-to-end data pipelines, automating ETL workflows, and performing data cleaning, preprocessing, and feature engineering. Strong background in statistical analysis, hypothesis testing, and A/B testing to uncover actionable insights and validate model effectiveness. Experienced in leveraging Azure Data Factory, Azure SQL Database, and Azure Data Lake for seamless data integration and large-scale data science workflows. Adept at creating impactful data visualizations using Matplotlib, Seaborn, and Tableau to drive data-driven decision-making. Innovative problem-solver with excellent communication skills and a proven ability to transform business requirements into scalable analytical solutions.

Experience

1. Ai Ml Engineer

   CHASE

   Feb 2025 — Present · NY, US

   Design and execution of machine learning projects to solve specific business challenges identified through collaboration with stakeholders.Applied machine learning algorithms such as linear regression, SVM, Naive Bayes, Random Forests, K-means, and KNN for data analysis and predictive modeling.Developed ETL packages using SSIS to transform, join, and prepare data for analysis, ensuring the availability of required features.Cleaned and preprocessed large datasets by handling missing values, outliers, and noise to ensure data quality for analysis and modeling.Conducted time series analysis using statistical models and machine learning techniques to forecast demand and optimize resource allocation.Designed and implemented scalable data pipelines in Azure Data Factory for seamless data ingestion, transformation, and integration across diverse sources.Utilized Azure Databricks and Apache Spark for big data processing, data transformation, and machine learning model development.Optimized cloud data storage solutions using Azure Data Lake and Azure Blob Storage for efficient data management and retrieval.Deployed machine learning models using Azure Machine Learning, integrating with Azure Databricks and Azure Synapse Analytics for end-to-end lifecycle management.Built predictive models for customer behavior using algorithms like Random Forests, XGBoost, and Support Vector Machines.Developed NLP pipelines for text preprocessing, tokenization, stemming, and lemmatization to prepare unstructured data for analysis.Designed and implemented deep learning models for image classification and text analysis using TensorFlow and Keras.

Education

• Saint Peter's University

  Masters

  2023 — 2025

• Jawaharlal Nehru Technological University

  Bachelor of Technology - BTech

  2017 — 2021