SUMMARY

• I have over 5yrs of experience as Data Scientist and 3 yrs of experience into Artificial Intelligence/Machine learning Algorithms.
• Good hands on experience on Software languages with Python, R studio. Highly accurate and experienced executing data - driven solutions to increase efficiency, accuracy, and utility of internal data processing adept at collecting, analyzing, and interpreting large datasets, developing new forecasting models, and performing data management tasks.
• Experienced at creating data regression models, using predictive data modeling, and analyzing data mining algorithms to deliver insights and implement action-oriented solutions to complex business problems
• Using machine learning techniques supervised, unsupervised, reinforcement learning and understand the requirement & design for AI/ML use cases
• Strong hands and exposure on experience in Python, (Frameworks/libs: NumPy, SciPy, Pandas, NumPy, Matplotlib/Plotly, scikit-learn, Statsmodels)
• Experinece on Data Preparation, modeling build, Feature Engineering and production/deploymnet
• Hands on experience in predictive analytics and statistical tools, machine learning algorithms and big data tools
• Use pandas for data analysis and sea born for statistical plots
• Experience with R studio (Frameworks/libs: Matrices, Data Frames, Lists, Data manipulation using Dplyr and Tidyr, Data visualization with ggplot2, Data input and output)
• Experience with Neural Networks, Naive Bayes, SVM, Decision Forests
• Experience delivering products or solutions that utilized Machine Learning, Natural Language Processing or other forms of AI (Artificial Intelligence) solutions like machine vision
• Strong experience in SQL ( using one of database pgadmin(postgreSQL), Cassandra, and oracle ) and Tableau
• Experience with one of Deep Learning (Tensor flow)
• Knowledge on different technology trends, salary trends, Big Data market and different job roles in Big Data
• Knowledge on complex architectures of Hadoop and its component
• Understand how Map Reduce, Hive and Pig can be used to analyze big data sets
• Sample data sets and scripts (HDFS commands, Hive sample queries, Pig sample queries, Data Pipeline sample queries)
• Running HDFS commands, Hive queries, Pig querie
• Understand modern data architecture: Data Lake
• Experience major components of GCP (Google cloud platform), know how to use Tensor Flow on cloud, understand machine learning fundamentals
• AWS and Highly skilled in CNN, RNNs & LSTMs, scikit-learn, keras, tensorflow.

PROFESSIONAL EXPERIENCE

Confidential, Irving, TX

Senior AI/Machine Learning Engineer

Responsibilities:

• Worked on PostgreSQL (pgAdmin), Cassandra (DataStax), SQL Developer tools to query and extract logs from BPM and MTAS database
• Built different use cases and extensively worked on Jupyter Notebook for Data Cleaning, converted data into structured format, removed outliers, dropped irrelevant columns & missing values, imputed missing values with median/mode/average/min/max other statistical methods
• Worked on libraries like NumPy, Pandas, SciKit Learn, mathplot,seaborn, psycopg2 etc.
• Using machine learning techniques supervised, unsupervised, reinforcement learning and understand the requirement & design for AI/ML use cases
• Develop AI/ML algorithms
• Developed and scaled machine learning and deep learning models like Logistic Regression, Random Forest, Gradient Boosting Machines, SVM (Support Vector Machines), etc. for classification
• Programmed using python to prototype and deploy Machine Learning, Deep Learning, Predictive models, Probabilistic and Statistical Modeling based approach with user interface development
• Build, train and deploy ML models on AWS with Amazon sage maker
• Designing and executing processes related to machine learning and predictive modeling, data mining, and research on large scale complex data sets using statistical models, graph models, text mining and other modern techniques
• End to end analytical solutions to the business problems. Understanding the problem, data and creating an analytical solution using statistical techniques in Python or R and providing recommendations.
• Used machine learning modelling techniques like GridSearchCV, SMOTE.
• Worked on CentOS7 and Linux to access the AWS EC2 instances.
• Created customized Tableau dashboards for daily/weekly/monthly reporting purposes.
• Perform unit testing and provide system test support and Validate & monitor deliverable in production
• Automated the ML model building process by building Data Pipelines further integrating it with Data cleaning process
• Used PuTTy for accessing the AWS EC2 instances for training the models with Production phase data
• Integrated the AWS server with GitLab in order to push the model into production and to monitor the performance
• Machine Learning model building is collaborated within the team through GitLab integration.
• Use Jira for project management teams such us report,& analysis, workflow customization, issue /task management, project customization and help to team of all types manage work
• Collaborates with business and team members to understand company needs, Employs predictive modeling, text mining, and forecasting techniques, Keeps up-to-date with analytics technology and understands their utility for daily
• Evaluate the method and technical solution of data analytics projects
• Design elegant data visualizations to present complex analysis and insights to customers with Tableau or other related tools
• Work closely with both onshore and offshore team

Confidential, NJ

Data scientist / Machine Learning Engineer

Responsibilities:

• Collaborate with ML Engineers and Data Scientist to build data and model pipelines and help in running machine learning tests and experiments
• Experience with Statistical Modeling, Data Extraction, Data cleaning, Data screening, Data Exploration and Data Visualization of structured and unstructured datasets
• Ability to implement large scale Deep Learning and Machine Learning algorithms to deliver resourceful insights and inferences
• Using machine learning techniques supervised, unsupervised, reinforcement learning as applied to the travel, transport or logistics industry
• Collaborates with business and team members to understand company needs, Employs predictive modeling, text mining, and forecasting techniques, Keeps up-to-date with analytics technology and understands their utility for daily
• Develop Machine Learning and NLP framework, models and service that are flexible to extend to new features
• Customize in-house NLP framework and skills according to product requirement
• Enhance Natural Language Understanding models with measurable metrics and deliver better results on user experience
• Ability to synthesize quantitative results to determine implications and make actionable recommendations
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Used predictive analytics such as machine learning and data mining techniques to forecast company sales of new products with a min 90% accuracy rate
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Tableau technologies
• Use data visualization tools (Pie, Histogram, Boxplot, ggplot2 and Bar plot,etc) to share ongoing insights
• Work closely with product owners and other team members to meet delivery goals
• Design elegant data visualizations to present complex analysis and insights to customers with Tableau or other related tools
• Build and configure SQL and Excel data spread sheet implanted into the business Strong hand on experience Microsoft “Office, Excel. Power point”
• Apply Machine Learning methodologies such us with R and Python and have solved several real-life problems using these. K Means, K Nearest, Linear regression, Logistic regression, Support vector machines, Decision Tree methods

Confidential, Dallas, TX

Data Scientist

Responsibilities:

• Act as a business consultant for the use of Data Analytics to drive business decisions, business strategy
• Using machine learning techniques supervised, unsupervised, reinforcement learning and understand the requirement
• Translating business needs to technical requirements and implementation
• Used predictive analytics such as machine learning and data mining techniques to forecast company sales of new products with a min 90% accuracy rate
• Apply data science approaches and methodologies (such as liner and logistic regression decision tress) to improve business outcomes
• Initiate ideas and develop related model with R
• Develop the data analysis model according to business scenarios
• Evaluate the method and technical solution of data analytics projects
• Design elegant data visualizations to present complex analysis and insights to customers with Tableau or other related tools
• Share the data science knowledge to other team members and build up the productive internal knowhow
• Discover the information hidden in vast amounts of data and help us make smarter decisions to deliver even better products
• Responsible for providing educational guidance and assistance for students by planning schedules, recommending courses and determining appropriate education solutions for different types of students. Prepares portfolio manager reports for assigned client review meetings. Delivers to advisor for review day prior to meeting. Back up to front desk, answers phones and Participate in company meetings