SUMMARY

• 9+ years hands - on experience in DataScience and Analytics including Big Query using, SQL,Data Collection, data warehousing, DataCleaning, Featurization, Feature Engineering DataMining, Machine learning and Statistical Analysis with large datasets of structured.
• Experience in developing a web application for internal use that centralized data acquisition, using HTML/CSS, Angular JS,TypeScript, and Agile software development.
• Strong experience in building CloudDataLake using AWS S3, AWS Glue, GlueDataCatalog Serverless Framework, Lambda, RDS, Aurora, EC2, SNS, SQS, IAM,ECS, CloudFormation, CloudWatch.
• Experienced in BigData Ecosystem with Hadoop, HDFS, MapReduce, Pig, Hive, HBase, Impala, Sqoop, Flume, Kafka, Oozie, Spark, PySpark and Spark Streaming.
• Expert in CoreJavawith in-depth knowledge of CoreJavaconcepts such as Multithreading, Synchronization, Collections and Event/Exception handling Experience in Software Development Life Cycle (SDLC) of Projects - System study, Analysis, Physical and Logical design, Resource Planning, Coding and implementing business applications
• Experience in real time data from various data sources throughKafkadata pipelines and applied various transformations to normalize the data stored in HDFS Data Lake.
• Theoretical foundations and practical hands-on projects related to (i) supervisedlearning(linear and logistic regression, boosted decision trees, Support Vector Machines, neural networks, NLP), (ii) unsupervisedlearning(clustering, dimensionality reduction, recommender systems), (iii) probability & statistics, experiment analysis
• Experience in creating complexdatapipeline process using T-SQL scripts,SSISpackages, Alteryx workflow, PL/SQL scripts, Cloud REST APIs, Python scripts, GCP Composer, GCP dataflow.
• Experience in Creating pipelines, data flows and complex data transformations and manipulations using ADF and PySpark withDatabricks.
• Experience with structured (MySQL, Oracle SQL, Postgre SQL) and unstructured (NoSQL) databases. Strong understanding of relational databases. Familiar with cross platforms ETL using Python/JAVASQL connector, PySpark Data Frame.
• Experience with container-based deployments using Docker, working with Docker images, Docker Hub and Docker-registries and Kubernetes.
• Experience in SQL Server Analysis Services (SSAS) and SQL Server Reporting Services (SSRS) tools.
• Experience implementing batch and real-timedatapipelines using AWS Services, S3, Lambda, DynamoDB, Redshift, EMR, kinesis
• Good knowledge in Apache Hadoop ecosystem components Spark,Cassandra, HDFS, Hive,SQOOP, Airflow.
• Knowledge on Google Cloud Platform (GCP) services like compute engine, cloud load balancing, cloud storage, cloud DataProc, Cloud Pub/Sub, cloud SQL, Big Query, stack driver monitoring and cloud deployment manager

PROFESSIONAL EXPERIENCE

Big Data Machine Learning Engineer

Confidential, New York City, NY

Responsibilities:

• Conduct in-depth exploration of data to determine opportunities for improvement and present recommendations to supervisor and client.
• Perform strategic data analysis and research in alignment with identified business needs and requirements.
• Expertly extract data from multiple databases, and manipulate and explore data utilizing quantitative, statistical, and visualization tools.
• Prioritize data by performing statistical analysis to determine data to be used.
• Create intuitive static and interactive visualizations using routine program monitoring data for websites, annual and quarterly reports, and presentation to stakeholders.
• Extract data from Big Data Hadoop Data Lake, and Excel, performing analysis, data cleansing, and sorting, merge reporting and expertly utilize Base SQL, Hive and Excel to create dashboards.
• Mathematical & Statistical Modeling
• Apply knowledge to select appropriate modeling techniques and effectively establish and maintain processes for validating /updating predictive models.
• Design and implemented statistical models, predictive models, enterprise data model, metadata solution and data life cycle management in both RDBMS, and Big Data environments.
• Skillfully utilized Spark, Scala, Hadoop, HBase, Kafka, Spark Streaming, Tensor Flow, MLLib, Python, a broad variety ofmachinelearningmethods including classifications, regressions, dimensionally reduction.
• Deliver expertise working on different data formats such as JSON, XML and performmachinelearningalgorithms in R.
• Application of variousmachinelearningalgorithms and statistical modeling like decision trees, text analytics, natural language processing (NLP), supervised and unsupervised, regression models, neural networks, deeplearning, SVM, clustering to identify Volume using scikit-learn package in python.
• Python REST API implementation using FLASK forMachinelearningmodels.
• Implemented different models like Logistic Regression, Random Forest and Gradient-Boost Trees to predict whether a given die will pass or fail the test.
• Perform data analysis by using Hive to retrieve the data from Hadoop cluster, SQL to retrieve data from the database and used ETL for data transformation.
• Perform Data Cleaning, features scaling, features engineering using pandas and numpy packages in python.
• Communicate the results with operations team for taking best decisions.
• Collect data needs and requirements by Interacting with the other departments.

Environment: Python 2.x, R, HDFS, Hadoop 2.3, Hive, Linux, Spark, Tableau Desktop, SQL Server 2012, Microsoft Excel, Spark SQL, PySpark.

Machine learning Engineer

Confidential, Austin, TX

Responsibilities:

• Gathering, retrieving and organizing data and using it to reach meaningful conclusions.
• Developed a system for collecting data and generating their findings into reports that improved the company.
• Setting up the analytics system to provide insights.
• Initially the data was stored in MongoDB. Later the data was moved to Elasticsearch.
• Used Kibana to visualize the data collected from Twitter using Twitter REST APIs.
• Conceptualized and created a knowledge graph database of news events extracted from tweets using Java, Virtuoso, Stanford CoreNLP, Apache Jena, RDF.
• Producing and maintaining internal and client-based reports.
• Creating stories with data that a non-technical team could also understand.
• Worked on Descriptive, Diagnostic, Predictive and Prescriptive analytics.
• Implementation of Character Recognition using Support vectormachinefor performance optimization.
• Monitored the Data quality and integrity of data was maintained to ensure effective functioning of department.
• Managed database design and implemented a comprehensive Star-Schema with shared dimensions.
• Utilized various techniques like Histogram, bar plot, Pie-Chart, Scatter plot, Box plots to determine the condition of the data.
• Building and testing hypothesis, ensuring statistical significance and building statistical models for business application.
• DevelopedMachineLearningalgorithms with Spark Mlib standalone and Python.
• Performed data pre-processing tasks like merging, sorting, finding outliers, missing value imputation, data normalization, making it ready for statistical analysis.
• Implemented variousmachinelearningmodels such as regression, classification, Tree based and Ensemble models.
• Performed model Tuning by adjusting the Hyper parameters and raised the model accuracy.
• Validated different models developed applying appropriate measures such as k-Fold cross validation, AUC, ROC to identify the best performing model.
• CreatedMachineLearningand statistical methods, (SVM, CRF, HMM, sequential tagging) or willingness to intensely learn.
• Designed and implemented end-to-end systems for Data Analytics and Automation, integrating custom visualization tools using R, Tableau, and Power BI.

Environment: Python 3, R Studio, MLLib, Regression, SQL Server, Hive, Hadoop Cluster, ETL, Tableau, NumPyPandas, Matplotlib, Power BI, Scikit-Learn, ggplot2, Shiny, TensorFlow, Teradata.

Data Engineer

Confidential, Harrishburgh, PA

Responsibilities:

• Experience in building and architecting multipleDatapipelines, end to end ETL and ELT process forDataingestion and transformation in GCP
• Strong understanding of AWS components such as EC2 and S3
• Implemented a Continuous Delivery pipeline with Docker and Git Hub
• Worked with g-cloud function with Python to loadDatain to Bigquery for on arrival csv files in GCS bucket
• Process and load bound and unboundDatafrom Google pub/sub topic to Bigquery using cloud Dataflow with Python.
• Devised simple and complex SQL scripts to check and validate Dataflow in various applications.
• PerformedDataAnalysis,DataMigration,DataCleansing, Transformation, Integration,DataImport, andDataExport through Python. good experience with ETL concepts, building ETL solutions andDatamodeling
• Architected several DAGs (Directed Acyclic Graph) for automating ETL pipelines
• Experience in fact dimensional modeling (Star schema, Snowflake schema), transactional modeling and SCD (Slowly changing dimension)
• Devised PL/SQL Stored Procedures, Functions, Triggers, Views and packages. Made use of Indexing, Aggregation and Materialized views to optimize query performance.
• Developed logistic regression models (Python) to predict subscription response rate based on customers variables like past transactions, response to prior mailings, promotions, demographics, interests, and hobbies, etc.
• Hands of experience in GCP, Big Query, GCS bucket, G - cloud function, clouddataflow, Pub/suB cloud shell, GSUTIL, BQ command line utilities,DataProc, Stack driver
• Implemented Apache Airflow for authoring, scheduling and monitoringDataPipelines
• Proficient in Machine Learning techniques (Decision Trees, Linear/Logistic Regressors) and Statistical Modeling
• Worked on confluence and Jira skilled indatavisualization like Matplotlib and seaborn library
• Hands on experience with bigdatatools like Hadoop, Spark, Hive
• Experience implementingmachinelearningback-end pipeline with Pandas, NumPy

Environment: GCP, Big query, Gcs Bucket, G-Cloud Function, Apache Beam, Cloud Dataflow, Cloud Shell, Gsutil, Docker, Kubernetes, AWS, Apache Airflow, Python, Pandas, Matplotlib, seaborn library, text mining, NumPy, Scikit-learn, Heat maps, Bar charts, Line charts, ETL workflows, linear regression, multivariate regression, Python, Scala, Spark

Software Engineer

Confidential, Columbus, IN

Responsibilities:

• Providing support to manage thesoftwareand database for all the warehouses operation and maintaining application servers, databases servers by applying patches from time to time
• Involved in preparing high level design documents, coding, analyzing business and enhancing my programming skills.
• Developed Python automation scripts to facilitate quality testing.
• Datawas loaded intoOraclepartitions based on monthlydata.
• Applied Oracle's Advanced Queuing to achieve integration at the application level, so that Java, C++, and PLSQL software components can interact using a shared messaging architecture.
• Wrote Python modules to extract/load assetdatafrom the MySQL source database.
• Worked with backed team to design, build and implement RESTFUL API's for various services.
• Analyzed business process workflows and assisted in the development of ETL procedures for mappingdatafrom source to target systems
• Gathering software requirements and communication with the client and their end users.
• Systems Analysis, Design, Software Engineering
• Database Design and Development in SQL Server, Oracle, Microsoft Access and MySQL.
• Programming in C/C++, C# and Visual Basic Programming Languages
• Website Based Solution and Development using C#/SQL Server, PHP/MySQL, and JavaScript.
• Manage Software Development Teams.
• Worked on Docker containers to package all the necessary applications in an image to setup initial workstation.
• Moving or copying the databases, detaching and attaching, backing and restoring databases.
• Involved in resolving ETL Production issues, performed its recovery steps and implemented in bug fixes.
• Performance tuning of complex SQL qairueries scheduled BI jobs according to the design flow using Control-M jobs.
• Worked withDataEngineersto submit SQL statements, import and exportdataand generate reports in SQL server.

Environment: Python, ETL, MySQL, SOAP, SQL, Netezza, Web Sphere, Web Services, Shell Script, Control-M