SUMMARY

• A Cloud Computing, Big Data, and Artificial Intelligence (AI) practitioner with 17+ years of experience, specializing in Migrating various type of analytics workloads from On - prem to Cloud or Inter Cloud, Big Data Analytics and Deep Learning.
• I have demonstrated leadership in conceptualizing and implementing various critical business use cases and create value for clients in Automotive, CPG, Financial Services, Insurance, Healthcare, Medical Devices, Pharmaceutical, and Retail industries.
• I bring perfect blend of Business and Technology skills that enable me to drive actionable insights from data to solve critical business problems.
• Furthermore, management consulting experience has enabled me to develop structural and critical thinking, C-level communication and presentation skills, and influence cross functional teams and decision makers using data driven approach.

TECHNICAL SKILLS

• VPC, Cloud Router, Cloud IAM, Google Compute Engine, Cloud Dataflow, Cloud Dataproc, Cloud Pub/Sub, Compute Engine, Cloud Storage, Cloud Bigtable, Cloud BigQuery, Cloud Datalab, Apache Beam, Cloud SQL, Cloud Run, Cloud Spanner, Cloud Data Fusion, Cloud DataPrep, Terraform, ISTIO, StackDriver, Cloud Composer/Apache Airflow, Firebase/Firestore, Kubernetes, Docker, CI/CD, Jenkins, Jira
• Analytic tools such as TensorFlow, PyTorch, Cafe2, CNTK, Keras, Azure ML Studio, MSFT R server, Cortana Intelligence Suite, IOT, Stream Analytics, IVR analytics, R, SAS, Python, Java, C/C++, Splunk,
• Data visualization tool -Tableau, Qlikview, Spotfire, and D3.js; Data science tools - pandas, numpy, sklearn
• Statistical Modeling, Outlier detection, Hypothesis testing, Machine Learning, Predictive Maintenance, Predictive Analytics, Risk Based Monitoring (RBM),Tesseract, Optimization, and Simulation
• Big Data analytics and technology stack such as Hadoop, Hive, Pig, HBASE,Yarn, Spark, Pyspark, Kafka, Stream, Kafka Connect, Elastic Search, Graph Database, Scala, Kudu, Solr etc.
• Cloud technologies - Azure, AWS, Google Cloud

PROFESSIONAL EXPERIENCE

Confidential

Cloud Solution Architect/Big Data Engineer

Responsibilities:

• Architected and develop a pipeline and machine learning algorithms on AWS cloud platform to process logfiles from ten thousand servers and predict server failure; Key tools used were Kafka, Spark Streaming, Spark, HBase
• Designed next generation on-prem BigData Anlaytics architecture using Spark over Kubernetes, S3, and state of art data science tools such as Tensorflow, Pytorch to process and drive insights from over petabytes of data
• Developed a solution to on AWS to index and search documents using solar/banana and Hadoop for a healthcare client that increased productivity by 15%
• Architected and built pipeline to process, digitalized, and Index thirty million scanned medical records to mine and search documents on AWS
• Developed pipeline on AWS platform using Hadoop framework to predict failure of Truck engine on the road that lead to reduction in warranty cost by $200M; data is streamed in real-time from engines to AWS cloud for analysis
• Architected and build next generation supply chain analytics platform using AWS(IaaS) and Cloudera Hadoop for a pharmaceutical company; configured VPC and firewall rules, Identify and Access Management rules, developed data ingestion, data processing, and data visualization approach that reduce cost by 10%
• Architected and implemented to migrate analytics reporting workload from on-prem to GCP cloud for a division of a media client; Key GCP components were BigQuery, Cloud Storage, CloudData Proc, Data Fusion, Cloud Composer/Apache Airflow, Cloud Dataflow/Apache Beam(Java), Stackdriver etc.
• Build data lake on GCP cloud platform; Configured VPC, created connectivity between on-prem data center and cloud, configured firewall rules, security rules, access control using Cloud IAM, defined encryption and key management strategy, configure auditing, monitoring, and logging mechanism using StackDriver
• Architected and implemented solution to ingest and analyze real-time IoT data from various sensors of a manufacturing plants to GCP cloud; the solution included various GCP components such as Cloud pub/sub, cloud dataflow/Apache Beam, Data Fusion, BigQuery, Data Studio, VPC, Cloud IAM, Stackdriver etc
• Developed Terraform script to deploy and manage Kubernetes cluster on GCP using GKE. Key modules were VPC, Firewall, Node configuration, Node-Pool configuration, container cluster, Load Balancer etc.
• Developed a deep learning models to classify adverse events (Text Classification) using Text Mining/Natural Language Processing for a pharmaceutical client that saved$3M in three years; the tools used were python, genism, tensorflow,
• Segment the products using product description using Text mining techniques such as tokenization and work frequency distribution for an e-commerce retailers to predict which customer will buy what product; the tools used were python, numpy, nltk etc.
• Mined social media text and news media text using text mining and natural language processing to understand the aggregate opinions of a $65B CPG client’s stakeholders - customers, investors, and consumers that reduced risk/threat/opportunity discovery and response time by 15% ; the tools used were python, tensorflow, genism, word2vec etc.
• Developed large scale deep learning models to extract texts from scanned electronic medical records (EMR) records and applied natural language processing (NLP) to convert unstructured data to structured data that enable physicians to identify potential cancer patient; the solution was developed on AWS platform
• Developed software and algorithm to understand driving pattern of drivers; data is being streaming from vehicle sensors to perform real-time analysis that is being used to determine insurance premium
• Architected and led development of trade promotion analytics using Big Data and advanced analytics technologies for global retailer to measure impact of various promotion types - online, mobile, display, and paper ads, for two millions SKUs in fifty markets and provided insights that resulted in increase in revenue by 15% and decrease in promotion cost by 30%
• Conceptualized and led implementation of one of the world’s largest customer insights platform to drive customer insights that enabled personalize customer experience across Omni-Channel, understand shoppers purchase behavior at store level, and tailor the merchandise to local demographic
• Developed Big Data strategy-people, process, technology, and right opportunity including developing roadmap, governance model, and setup elastic organization structure for a CPG client that secured $1M corporate funding to implement the strategy

Confidential

Principal Cloud Architect /Data Engineer/ Data Scientist

Responsibilities:

• Developed “Propensity to Buy” model using advanced analytics techniques for a leading retailer having >3000 stores that improve customer response rate by 6% during campaign period and ROI by 10%
• Developed “Macro Space Planning” model for a leading retailer to improve in store “space productivity” that reduced inventory in low volume stores by 40% and increased revenue in normal stores by 5%
• Built a recommendation system for e-commerce division of a large retailer that increased revenue by 3%
• Developed advanced analytics model for a large telecom player to analyze near real time CDR records that helped to identify high value customers, improve customer experience, and develop new products
• Evaluated advanced analytics platform for a $40B CPG client to aggregate data from disparate sources
• Collaborated with five member team of a $80B US investment bank to identify Big Data and Advanced Analytics Platform to reduce data management cost by 10%

Confidential

Management Consultant

Responsibilities:

• Assisted a $25B auto manufacturer to develop Big Data use cases and implementation roadmap that reduced warranty cost by 5% and customer service time by10%
• Assisted e-commerce division of a retail client to optimize online product portfolio and performed competitive analysis
• Developed corporate strategy and new growth opportunities for a $2B electronics component manufacturer that doubled the stock price in one year
• Advised lubricant division of a $350B global energy client to develop long term corporate strategy that resulted in portfolio of ideas with multiple time horizons and identification of innovative business models
• Collaborated with 10-member team of diversified industrial client to increase revenue by 20% and profit by 15%

Confidential

Founder and CEO

Responsibilities:

• The objective of the company was to provide remote patient monitoring service in emerging market
• Developed business case and financial models and pitched to venture capitalists
• Raised $500K from angel investors to develop prototype of device and monitoring software
• Collaborated with leading R&D centers in Europe and negotiated price and technology transfer terms