SUMMARY:

• A proactive person seeking an opportunity to work as a Machine Learning/ Data Scientist utilizing analytical & statistical skills and relevant expertise to help the company achieve business goals while sticking to vision, mission and values.
• Proficient in algorithm and design techniques.
• Ability to document ML project requirements and assess deliverable timelines.
• Proficiency in manipulating and analyzing complex, high - volume, high-dimensionality data from varying sources.
• Perform data cleaning and data transformation activities using Python and R
• Visualization of big data in Python matplotlib and Tableau.
• Practitioner of Data Mining methodologies like Cross Industry Standard Process for Data Mining (CRISP-DM) and Knowledge Discovery in Databases (KDD)
• Practitioner of Software Life Cycle Development (SDLC) process using different approaches like Waterfall, Agile, SCRUM and Test Driven Development (TDD).
• Proficient in MS Office applications (Word, Excel, PowerPoint, Access, Project)
• Experienced in presenting in an accessible way to executive-level stakeholders and colleagues alike to gain their support for data-driven initiatives and strategies.
• Guiding team members in implementation and execution of machine learning models at different levels of project life cycle.
• Highly motivated and a self-starter with effective communication and organizational skills
• Experienced in working with both technical and non-technical team members.
• Tutored high school and undergrad students for 6 years. Good team player and can handle a group as well.

TECHNICAL SKILLS:

PROGRAMMING LANGUAGES: Python, Java, C, C++

MACHINE LEARNING: Machine Learning Techniques such as Data Preprocessing (Data Cleaning), Regression models, Classification, Clustering, Association Rule learning (Apriori and Eclat), Reinforcement Learning (UCB and Thompsons Sampling), Natural Language Processing (NLTK, SpaCy), Text Mining, Data Extraction, Predictive Modeling, Statistical Modeling, Dimensionality Reduction (PCA and SVD) and Recommender Systems (Collaborative Filtering) .

DEEP LEARNING: NLP algorithms coupled with Deep Learning (ANN and CNN), Time Series Analysis, Speech and Text Analysis (RNN, LSTM), SOMs, Recommender Systems (RBM, Auto Encoders), libraries such as Keras, Tensorflow and PyTorch

DATABASE: MySQL, Apache Spark, NoSQL (MongoDB)

IDE: Anaconda - Spyder, IPython / Jupyter, Eclipse

EXPERIENCE:

Confidential, Cypress, TX

Sr. Data Scientist

Responsibilities:

• Mentored large scale data and analytics using advanced statistical and machine learning models.
• Designed a Request Analysis model using Natural Language Processing (NLP)’s nltk and spacy.
• Classified the image requests using CNN Classifier.
• Developed a predictive model using Random Forest Regression to predict the upcoming month’s claims and possible policy cancellations using XG Boost.
• Achieved efficiency of 86.2% in churning problem using XG Boost.
• Performed Data Cleaning to large quantity of data. Monitored the data using MySQL and Mongo DB.
• Worked with Data Visualization team which used Tableau, Performed data visualization using matplotlib.pyplot and Seaborn
• Discover patterns, formulate and test hypotheses, translate results into strategies which drive growth resulting in increased revenues and customer satisfaction.
• Interpreted complex simulation data using statistical methods.

Environment: Python 3, numpy, pandas, matplotlib, scikit-learn, Spyder, Jupyter, Apache - Spark, mllib, CART, Random Forest, XG Boost, NLP, NLTK, Bag of Words, SpaCy, Deep Learning, Keras, Tensorflow, PyTorch, PySpark, Jira, MySQL.

Sr. Data Analyst

Confidential, Tampa, FL

Responsibilities:

• Involved in Business discussions, Architecture discussions and writing the Business requirement document.
• Worked very closely with process teams and Business analysts in understanding the functional requirements
• Developed Business System Design Document and Solution Specification Document
• Performed data modeling and developed Analytical views for the transactional data, Attribute views for the master data, and the calculation views as final model in HANA Studio.
• Implemented SAP HANA data provisioning/replication technologies using SAP Landscape Transformation (SLT) and Direct Extractor Connection (DXC)
• Implemented SAP HANA Smart Data Access for Near-Line storage
• Provide insight on new technology and how it can be leveraged appropriately to improve the current environment

Environment: Python 3x, Anaconda - Spyder, Apache - Spark, Eclipse, TF-IDF, Association Rule Learning, Apriori, pyspark, numpy, pandas, scikit - learn, Eclipse, Regression, CART, MySQL, Dynamo DB

Confidential

Machine Learning Engineer - Intern

Responsibilities:

• Collected and analyzed large amount of data from all states of India.
• Performed Data Preprocessing and Data Cleaning and organized the collected data.
• Classified and organized the data with respect to gender, region (urban and rural), financial report, religion and caste.
• Applied machine learning (clustering) and statistical models to the collected data.
• Created Data classes and DB tables for integrating with external systems using MySQL
• Worked in Agile Methodology development

Environment: Python 2.7, Java, Eclipse, Anaconda - Spyder, MySQL, Agile

Confidential

Machine Learning Engineer

Responsibilities:

• Worked on end to end creation of the application.
• Worked with huge datasets. Performed data cleaning and preprocessing.
• Developed Use Case diagrams, Class diagrams and Sequence diagrams to express the detail design.
• Identify reusable components and implement accordingly.
• Involved in Agile Methodology development including Design, Systems Development, Testing, Systems Integration, Installation and Deployment.
• Created Data classes and DB tables for integrating with external systems using MySQL
• Involved in Integration - Connecting to systems internally and external to the organization.

Environment: Python 2.7, Java, Eclipse, Anaconda - Spyder, MySQL, Agile