* Primary working on new age machine learning/deep learning solutions in banking, insurance domain
* Focused on cutting age language models, computer vision models to deliver Saas products 
* Using primarily AWS cloud and working with sagemaker for model management.

Lead Data Scientist

Mentoring and Pair Programming with students/developers from online portal which are located all around the globe. Built data pipelines for ETL to consume terabytes of data using Hadoop ecosystem, also designed TDD environment Gave 100+ session with a rating of 5.0/5.0. Featured in Top 10 Java Experts on their website. Profile: https://www.codementor.io/devd

Data Science Mentor

* Deep learning research especially for text mining * Product development and future enhancements to the existing platform

Sr. Machine Learning Researcher

Data Engineer

Scraping web for posts and republishing them in KDnuggets predefined format, also designed structured way to resolve common HTML5 formatting issues. Managing the social media channels for KDnuggets. I have written posts for current topics which are mainly focused on data science MOOCs, and Social Network Analysis. Which helped thousands of users for understanding data science, resource for it and advance techniques.

Contributing Editor

Conceptualized and built a system to measure the digital effectiveness of insurance companies. Formulate the matrices and collected data from different APIs, performed data analysis and quantified them into a single score using Apache spark, nodejs and Angularjs Built a dashboard to show the comparison between different markets and companies using HiCharts

Data Science Intern

Scraping web for posts and republishing them in KDnuggets predefined format, also designed structured way to resolve common HTML5 formatting issues. I have written posts for current topics which are mainly focused on data science MOOCs, and Social Network Analysis. Which helped thousands of users for understanding data science, resource for it and advance techniques.

Data Science Intern & Blogger

Application Developer (web application, Data Modelling & REST based Service development) Developed data model for fast retrieval and analysis using Cassandra, Python, and Spark Developed web services for presenting data and real-time analytics results Followed test driven development, extreme coding and pair programming principles. Designed and implemented web flow in Spring and implementation of database using Hibernate Understanding of the semantic web architecture RDF and OWLs. Updating and developing REST apis. Enhanced the real time notification system with new notifications, using Cassandra, Tapestry, mysql and atmosphere.

Software Engineer

* Started learning the machine learning and building models during my third year of engineering, built my own model based on HMM to detect the dynamic gestures for controlling computers
* I then worked on learning data science and machine learning via online course during my first job while commuting for 2 hours I used to watch and complete them. I had gotten 12 certificates from Coursera, Edx and Udacity by the time I joined my masters program in 2015
* In NUS while doing my KDNuggets editorial work I came in touch with deep learning and since then I am constantly learning, implementing and deploying these models in images, NLP and time series based use-cases
* During my jobs my primary focus has been to work on pilots and exploring new opportunities for business and build products which would simplify business issues at scale
* My work includes statistical modelling on IoT data, financial and risk modelling based on explainable models(models which are not black box for business) as well

* My exposure to NLP first started at university and I was doing an internship at (2015-2016). I mainly worked on insurance products and building social media analytics for them. As part of this dashboard I developed a sentiment analysis view and one for tracking active Twitter with company hashtags in them. We would classify tweets into service tickets, celebration or emergency. This helped companies effectively work with their social media. 
* My next touchpoint contact at NLP was at SAP 1 year after my initial stint. In SAP, I got to use and build models for deep learning. I build models to match candidates and resumes, doing Word2Vec embeddings, and then prioritise the resumes based on WMD distances. Similarly, for candidates who are looking for resumes, we built job built this was productionized using TF-IDF as WMD had O(n^3) complexity. I also experimented with Siamese networks, Q&A kinds of models during this phase. 
*  I used to work on the side projects with the latest findings in fields like BERT, attention models in NLP, ELMO, NER tagging models as well as APIs from OpenAI, AWS and Google. 
* In 2021, got an opportunity to leverage my NLP skills one more time, this time in the first phase of text extraction from log books and daily reports on container vessels. In the second phase, I tried to build recommendations based on the vessel engine parameters and reports from crew. 
* In my current startup we are demoing the potential of NLP in the insurance industry. We build tools to do claim prioritisation based on user details from their policy details and try to match those items in claims. We do detect fraud in the claim process using the matching for hospital records to other details like description of diseases of patients and their billing details.
* In recent years I have been focusing increasingly on LLMs and conversational models, these focused not only reusing the pretrained embedding models like OpenAI GPT2/3, but also training own models

Personal details

Devendra D.

Summary

Technical skills

Work Experience