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Surendra Y - Sr Python/Data Scientist

[email protected]

Location: Fremont, California, USA

Relocation: Remote/Hybrid

Visa: H1B

Surendra Babu Yeluri Innovation and automation play a greater role than hard work Python Developer/Data Scientist ([email protected] +1-510-269-8097 Bay Area, CA PST) Summary: Over 15+ Years of experience in the field of Information Technology with Python, Machine Learning, NLP, Deep Learning, and AWS. Involved in all phases of the SDLC (Software Development Life Cycle) from analysis, design, development, testing, and maintenance with timely delivery. Experience using git and Jira for managing a software project. Hands-on experience using Pandas, NumPy, SciPy, Matplotlib, and Scikit-learn for developing various algorithms and utilizing machine learning algorithms. Strong expertise in Math/ Statistics, Machine Learning, and Predictive Modelling (Regression, Neural Networks, etc.) which are highly valuable. Strong Knowledge of Regression/ Linear Analysis Familiarity with any of Deep Learning, Generalized Linear Models, K- Mean, and naive Bayes. Created visualizations, reports, and technical documentation appropriate to data and reporting requirements. Involved in utilizing Machine Learning techniques like SVM, Naive Bayes, decision tree, Random Forest, XGBoost, and Gradient boost to classify data. Proficient in data visualization tools such as Tableau, Python Matplotlib, and Python Seaborn to create visually powerful and actionable interactive reports and dashboards. Experienced in managing applications by implementing AWS services which include EC2, S3, RDS, IAM, Redshift, CloudFormation, CloudWatch, SNS, SQS, Lambda, and Aurora postures. Hands-on experience in AWS, Big Query, cloud dataflow, and Extensive experience working with RDBMS such as SQL Server, MySQL, Oracle, and NoSQL databases such as MongoDB. Involved in configuration of VPC, ELB, EC2, SES, S3, IAM, RDS, and Inbound rules in AWS cloud services and configuring Experienced with working on NLP projects and using NLTK, and Spacy libraries. Exposure to ML models such as random forest, XGBoost, LightGBM, and other ensemble modeling algorithms. NLP Preprocess extracted data to ensure it is in a format suitable for NLP tasks, including tokenization, lemmatization, and entity recognition. Worked on different models for ride price, sentiment analysis, membership churn out, license plate recognition using NLP and Computer vision. Used Python scrappy library for scraping multiple websites for getting data ML Models Worked on chatbots, Q&A, Sentiment analysis using LLM, BERT & Gen AI Built Tableau/Looker dashboard using heat maps, tree maps, circle views, bar charts, lines, pie charts, area charts, box and whisker, Gantts, bubbles and highlight tables, symbols and filled maps according to ML models. Technical Expertise: Machine Learning, NLP, Deep Learning, Statistical Analysis, Numpy, Scikit-learn, OpenCV, TensorFlow, Keras, Regression Models Linear & Logistic, Customer profiling, segmentation & Clustering (Kmeans, Hierarchical), Decision Tree, Time Series forecasting Statistical methods such as ARIMA, Exp. Smoothing Methods, Bagging & Boosting, ML Forecasting methods such as ANN, RNN, CNN, LSTM, NLP, Computer Vision, LLM, BERT, Gen AI, Django, Flask, AWS, Tableau, Looker, SAP BI, GitHub, Hive, Oracle, Presto, Teradata, Pyspark, SparkSQL Experience: Lyft, Bay Area, CA (Python/ Data Scientist) Feb 21- Till Date Responsibilities: Transformed data science prototypes and applied appropriate ML algorithms and tools. Used Object Oriented Programming (Python), Unix scripting, or related programming languages. Used libraries such as Pandas, NumPy, SciPy, NLTK, and Spacy for data wrangling. Built ML models such as random forest, XGBoost, LightGBM, and other ensemble modeling algorithms. Responsible for Functional knowledge of unstructured data sets, including how to gather and clean them. Spin up EC2, VPC, Subnets, S3, and Inbound rules in AWS Setup Redshift database (RDS) in AWS and wrote complex queries on RDS. Written complex SQL queries for KPI and PL/SQL procedures to load/manipulate the data Worked on data movement technologies (ETL/ELT), Messaging/Streaming Technologies (AWS SQS, Kinesis/Kafka), Relational and NoSQL databases (Cassandra, Elastic Search, Graph database), API and in-memory technologies. Data modeling like Linear Regression, Logistic Regression, Decision Tree, Random Forest, XG BOOST, CAT BOOST, Ada BOOST, SVM, Clustering, etc. Built machine learning models to identify fraudulent applications for loan pre-approvals and to identify fraudulent credit card transactions using the history of customer transactions with supervised learning methods. Tackled highly imbalanced Fraud dataset using sampling techniques like under-sampling and oversampling with SMOTE (Synthetic Minority Over-Sampling Technique) using Python Scikit-learn. Used PCA and other feature engineering techniques to reduce the high dimensional data, feature normalization techniques, and label encoding with the Scikit-learn library in Python. Built Webframe work using Flask in Python and used Git and Jira for managing a software project. Applied different classification techniques like SVM, random forest, and Naive Bayes to classify the data, and for Developed the testing framework to show the model s ability and accuracy. Performing machine learning algorithms and advanced statistics such as regression, time-series forecasting, clustering, decision trees, exploratory data analysis methodology, simulation, scenario analysis, modeling, optimization, unstructured data analysis, and neural networks. NLP Preprocess extracted data to ensure it is in a format suitable for NLP tasks, including tokenization, lemmatization, and entity recognition and worked on Sentiment analysis for customer feedback and improved the services Built model to detect drive License plate by using in CNN/RNN and computer vision Worked on chatbot implementation using LLM/BERT Used Python libraries to web scrap and get data for ML algorithms. Env: Python, ML, NLP, Flask, Deep Learning, SciPy, TensorFlow, Keras, Spacy, LLM, Gen AI, AWS, RDS, Computer vision, PostgreSQL, AirFlow, Tableau. Rally Healthcare, Bay Area, CA (Python/ML Developer) Jan 20- Feb 21 Used Python libraries such as Pandas, NumPy, NLTK, and spacy for data wrangling and developed sentiment analysis Participated in all phases of data mining; data collection, data cleaning, developing models, validation, visualization, and performed Gap analysis. Worked on data pre-processing and cleaning the data to perform feature engineering and performed data imputation techniques for the missing values in the dataset using Python Developed Experiment design with Hypothesis Testing workflow, Clustering algorithms, and Support Vector Machines that improved Customer segmentation and Market Expansion. Built multiple ML models such as Linear, Logistical, random forest, and SVM. Set up EC2 & Load balancers for deploying web apps in the AWS server and set up group rules. Worked on automating Tableau jobs for backup of the data/repository every day and user onboarding automation using Python. Built routes using Flask framework in Python for this rally health fitness app and scaled up to enterprise level. Performed Exploratory Data Analysis (EDA) to visualize through various plots and graphs using Matplotlib and Seaborn library of Python, and to understand and discover the patterns in the Data, understanding correlation in the features using heatmap, performed hypothesis testing to check the significance of the features. Develop Statistical inference to test hypotheses for statistical analysis, data science, and Data Storyteller, Mining Data from different Data Sources such as SQL Server, Oracle, Cube Database, Web Analytics, and Hadoop. Built ML model for customer churn out and increased the membership Designed rich data visualizations to model data into human-readable form with Tableau and Matplotlib. Env: Python, Flask, ML, Pandas, NumPy, SciPy, AWS, RDS, Tableau, Looker, Hive, PostgreSQL, and Presto. Efulgent Systems, Bay Area, CA (Client MicroFocus/Lyft: Python ML developer/AWS) Aug 17- Jan 20 Experience in Object Oriented Programming (Scala, Python), Unix scripting or related programming languages and exposure to some of Python s ML ecosystem (Numpy, panda, sklearn, TensorFlow, etc.). Experience with object-oriented concepts in Python, and understanding and practical usage of design patterns. Worked on data pre-processing and cleaning the data to perform feature engineering and performed data imputation techniques for the missing values in the dataset using Python Worked on multiple models for sentiment analysis and fraud detection and recommendation engine Used libraries such as Pandas and NumPy for data wrangling and used SQL skills to manipulate large data sets Incorporated various machine learning algorithms and advanced statistical analysis like decision trees, regression models, SVM, clustering using Scikit-learn package in Python Worked on different data formats such as JSON, XML, CSV, .dat and exported the data into data visualization/ ETL platform Written multiple python/API scripts using python to connect to Tableau to refresh/extract the data Environment: Python, ML, NLP, AWS, TensorFlow, Keras, Oracle, Teradata, Windows Server, Cloud. NTT DATA (Client: Pearson Education; BCBS NC; RLI Corp: Python/BO Architect/Tableau Developer) Nov 11 - Jul 17 Created dashboards, charts, map reporting, and gauges using Xcelsius 2008 for complex data Created new users, groups, folders in CMC while upgrading to BO XIR4. Worked on gathering Business Requirements and prepared Functional Design Documents and Technical Design Documents. Created dashboards for executives and scheduled the dashboards and created KPIs. Experience Implementing Proactive Tableau Environment Health Checks and Performance Threshold Alerting Tableau User Group and User Entitlement Administration Experience with Tableau application performance monitoring, capacity planning, and tuning for multiple projects Worked with Alteryx to create ETL and created reports in Tableau and BO Worked on Linux platform and created multiple python scripts to automate jobs Environment: Business Objects 3.0/4.0, Tableau 9.3, Alteryx, Python, MS SQL, Oracle, Windows Server. WIPRO LTD (Client: Drugstore; Sony Electronics: SAP BI Developer) Oct 07- Nov 11 Created universes on BEX Query/Infocubes/Multiproviders and created WEBI reports Created dashboards, charts, map reporting, and gauges using Xcelsius 2008 for complex data Created new users, groups, and folders in CMC while upgrading to BO XIR3. Developed Dashboards, Complex and business Critical reports for Sales, Inventory, Pricing, and Accounting Teams using Business Objects and Tableau tools. Developed Reports Using Tableau for Marketing and Business Analytics Groups. Environment: SAP BO XI R2, 3.1, Oracle 11/10g, PL/SQL, TOAD, Windows, SAP BO 3.1. Education: Qualification: Bachelor's in Computers Science, Osmania Univ (Pass Out Year: 2001) India. Keywords: artificial intelligence machine learning business intelligence sthree information technology microsoft procedural language California North Carolina