Summary
Overview
Work History
Education
Skills
Majorstrengths
Timeline
Generic

JAYAGANESH GOVINDARAJ

Edison,USA

Summary

Data Scientist with an experience of over 14 years in various domains and industries like Payments, Financial Services, Insurance, Healthcare, Manufacturing, Internet-related services and products etc. Acquired and applied expert level knowledge in Deep Learning, Machine Learning, Data Clustering, Natural Language Processing and Probabilistic graphical models. Have a very strong AI product development experience using languages like Python, Java, Scala and APIs like TensorFlow, Sklearn, Pandas, Apache Spark etc. Involved in developing State of the art solutions. A polyglot programmer, have an immense experience in programming language starts from Assembly languages to modern day languages. Hence, have strong nuances on programming evolution and paradigms. AI Lead Direct and lead to set up an AI laboratory in Altimetrik and lead to developing multiple AI accelerators. AI lab made a huge impact and due to that, Gartner featured Altimetrik on a list of 32 most visible DS and ML providers in the world during the period 2017 - 2018.

Overview

17
17
years of professional experience

Work History

Principal Data Scientist

Synechron
11.2017 - Current
  • Company Overview: Developing and designing Artificial Intelligence Solutions for the Financial Services Industry
  • Launched AI accelerators ‘NEO’ for financial industry
  • I am recruited to develop and manage AI Accelerator ‘NEO’
  • I am leading this project
  • This project involves 80% technical and 20% management
  • I am involving to work with different level of data scientists and engineers that includes Algorithm design, hybrid model development, optimization selection, model evaluation, A/B testing and process reiteration
  • As part of this product development, I have a chance to work on the following projects
  • Vertical Search Engine Enhancing search engine components like Synonym Expansion, Alternative Query generation, Automatic query suggestions, Relevant search results etc
  • Using neural search algorithms
  • Automated Data Extraction uses NLP to achieve automated data extraction and intent realization, allowing firms to pull data from earnings reports and other sources and contextualize its intent
  • Chatbot Framework Developing generic Chatbot framework, this framework is designed and developed in such a way that it should be applicable for any business use cases
  • Automated Financial Advice Generation can be achieved by using NLP to extract CRM data and NLG to reach a compliant conclusion through real-time queries and contextual user information
  • Automated Executive Summaries written in plain language using NLP and NLG
  • Customer Insights has four Modules for Banks, Credit Cards, eCommerce and Mortgages that allow banks to bring together their Know-Your-Customer (KYC), Banking and Credit Card Data into a database, and join them with the customer’s online behavior (if opts in) via web and social platforms
  • Product Recommendation uses behavioral analysis to understand customer patterns for new client acquisition
  • AML/Fraud Detection uses AI and behavioral analysis to identify potentially suspicious activity indicative of money laundering and fraud
  • Developing and designing Artificial Intelligence Solutions for the Financial Services Industry
  • Launched AI accelerators ‘NEO’ for financial industry
  • As a Principal Scientist, contributed most of my time in AI component design, participated in the business discussion to understand the nature of data components, data regulations in financial services
  • Involved in developing machine learning programs, parameter and hyper-parameter optimization components, and model evaluation components
  • Had a chance to work in most of the state of the art deep learning architecture
  • Also, rebuilt most of the core components using state of the art architecture
  • Set up and manage AI development and production infrastructure
  • Help AI product managers and business stakeholders understand the limitations
  • Helped to build data ingest and data transformation infrastructure
  • Keep current of the latest AI research relevant to the Financial service domain

Artificial Intelligence Lead

Altimetrik
07.2016 - 11.2017
  • Company Overview: Developed an abstraction framework for both technical and non-technical people, allowing users to create complicated ML pipelines
  • Altisolve is an abstraction framework
  • We developed this product for both technical and non-technical people
  • It’s an Informatica-like environment with Various ML and DL components and the user can drag and drop the components, set the parameters, hyper parameters etc
  • User can use this tool and create any complicated ML pipelines
  • They can convert the pipelines into source code on various languages
  • Also, it has an option to run the algorithm in a distributed cluster, GPU machine or an individual machine
  • Developed an abstraction framework for both technical and non-technical people, allowing users to create complicated ML pipelines
  • 30+ developers worked on this project
  • I lead the technical team and an active developer throughout the product development
  • Designed architecture for this framework, developed most of the Machine learning and distributed programming core components
  • Developed parameter, hyper-parameter optimization components, and evaluation strategy
  • Developed testing framework to test Machine learning programs
  • Integrated the core application, designed and maintained the integration strategy
  • Designed and built deployment components, collaborated with DevOps on these activities
  • Helped to deploy Altisolve in the client environment

Artificial Intelligence Lead

Altimetrik
12.2016 - 06.2017
  • Company Overview: Developed Clara, an Enterprise Artificial Intelligence Bot for Mercedes Benz, as a generic framework for multiple use cases
  • Clara is an Enterprise Artificial Intelligence Bot developed for Mercedes Benz
  • We developed this product as a generic framework so that multiple use cases can be handled
  • Developed components like Annotation tools, Intent classifier, Mention Extractor, Slot filler, Answer processor and Dialog Manager
  • I have created a generic design patterns to ease the development and productivity
  • Developed Clara, an Enterprise Artificial Intelligence Bot for Mercedes Benz, as a generic framework for multiple use cases
  • Developed State based Rule engine in Python
  • Worked in Intent and Mention Extractor
  • Used traditional and standard algorithms to develop the NLP components
  • Worked on integrating all the components with Dialog Manager
  • Developed a Chatbot dashboard
  • Developed a test framework using Python to test Machine Learning and integration components
  • Developed parameter, hyper-parameter optimization components, and evaluation strategy
  • Developed Monitoring system and integrate the models with Node JS for real-time prediction
  • Worked with business as part of post-implementation support

Artificial Intelligence Lead

Altimetrik
07.2016 - 02.2017
  • Company Overview: Created customer 360 views across multiple regions for Daimler AG, focusing on data ingestion, integration, and governance
  • This project is to create customer 360 views across multiple regions for Daimler AG, it required skills in Data ingestion, integration, virtualization, quality, governance, stewardship, security etc
  • I mostly worked with business and prepared a detailed architecture
  • Created customer 360 views across multiple regions for Daimler AG, focusing on data ingestion, integration, and governance
  • Attended multiple workshops with clients across regions like Germany, Singapore, United States and China
  • Understand the existing system and choose what is existing, what can newly add etc
  • Analyzed where Data science can apply in the system like matching engine, Automatic stewardship, auto quality check etc
  • Hence it involved integration between multiple countries, analyzed and suggested tool set to handle regulations like GDPR, US federal regulations etc
  • Hand over the necessary details to the peers who involved in development
  • Created tool set to understand the data across regions

Senior Data Scientist

DXC Technology
06.2010 - 07.2016
  • Company Overview: Worked on data analytics and machine learning for Zurich Farmers Insurance company, focusing on data extraction and reporting
  • Zurich Farmers Insurance company uses SAS files as an analytics storage
  • We use SAS Modules to extract the data from transactional database to warehousing tables and historical database tables to DB2
  • For Ad-hoc and daily off-line jobs, we maintained Batch SAS processing system to retrieve, clean, preprocess and profiling
  • The cleaned data would be stored in SAS file system, and the same would be using to produce reports for business, also, we provide Ad-hoc jobs for on-demand work items
  • Some of the on-demand items are, Marketing campaign reports, Renewal prediction reports, Claim Fraudulent detection reports, Regulatory reports, Claim processing reports, Forecasting reports, Claims and Loss Reports
  • Worked on data analytics and machine learning for Zurich Farmers Insurance company, focusing on data extraction and reporting
  • Also, Zurich initiated a new Data warehousing system instead of Conventional database system due to the volume data increases every year which drastically affected processing times on the data warehousing extractions
  • This leads to migrating the conventional extraction and processing to the Hadoop Eco-system
  • Transactional and Secured data was maintained in the conventional system which uses by the front-end web applications
  • Customer data stored in the Hadoop file system for reporting and analytics
  • Batch processing system used Sqoop, Hive, Spark jobs to retrieve the data from application transactional database and stores the data into Hadoop Eco-system in HDFS, and HBase
  • Mostly worked in Statistical and ML algorithms (Machine learning, NLP), also in Big data ecosystems like MR, Pig, Hive, Spark
  • Mostly worked with business, understand requirements, define ML algorithms, and coding using the real-world languages
  • Also, involved to work with research team on Machine Learning algorithms and distributed programming

Analyst Programmer

Syntel
10.2007 - 06.2010
  • Company Overview: Worked on data mining and analytics for WellPoint Health insurance company, focusing on membership and claim processing
  • The WellPoint Health insurance company uses SAS and R programming for their data mining and data analytics
  • Worked as a Analytics SME on Membership and Claim processing
  • Also, had a chance to work various regulations like HIPAA, ICD
  • Worked on data mining and analytics for WellPoint Health insurance company, focusing on membership and claim processing
  • Full-time analyst where I worked in languages like SAS, R Programming, Java, also involved in multiple assignments in terms of Analytics
  • Had a chance to work in Informatica, and IBM Mainframe to create Analytics Data Warehouse

Education

B.E. - Electrical Engineering

Anna University
01.2007

Skills

  • Deep Learning Frameworks (TensorFlow, Keras, DL4J)
  • ML and statistical Frameworks (Sklearn, numpy, pandas, stats-model, matplotlib etc)
  • GPU Programming
  • Machine and Deep Learning
  • NLP
  • Reinforcement Learning
  • Python
  • Cython
  • Flask
  • Docker
  • Kubernetes
  • Terraform
  • JAVA
  • Spring
  • Scala
  • Play
  • JavaScript
  • Node JS
  • Angular
  • C
  • C
  • R Programming
  • SAS
  • IBM Watson
  • AWS
  • Azure
  • Tableau
  • Hadoop
  • Apache Spark
  • Kafka
  • Informatica
  • Shell Scripting
  • SQL Server
  • MySQL
  • IBM DB2
  • MongoDB
  • Elastic Search
  • Linux Admin Tools

Majorstrengths

  • Lead the high quality data science team with a team size of 15+ both in Synechron as well as in Altimetrik.
  • Very good experience to lead high-profile data science team on various projects.
  • Deep and thorough knowledge in Statistical distributions and mathematical optimizations.
  • Contributing to well known open sources like Pandas, Scikit Learn, and Scala language etc.
  • Very good knowledge in Statistical and Probabilistic models.
  • Good knowledge in Machine Learning design patterns.
  • Strong work experience in Research and Development space.
  • Strong experience in parallel and distributed programming.
  • Have a very good knowledge in Data Structures and Algorithms.

Timeline

Principal Data Scientist

Synechron
11.2017 - Current

Artificial Intelligence Lead

Altimetrik
12.2016 - 06.2017

Artificial Intelligence Lead

Altimetrik
07.2016 - 11.2017

Artificial Intelligence Lead

Altimetrik
07.2016 - 02.2017

Senior Data Scientist

DXC Technology
06.2010 - 07.2016

Analyst Programmer

Syntel
10.2007 - 06.2010

B.E. - Electrical Engineering

Anna University

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JAYAGANESH GOVINDARAJ