December 2021 - Present
Built an internal portal to Automate the Marketing campaigns of
• Technically led a team of 5 internals and 10+ external colleagues (Data Scientists, Data Engineers, UI/UX Developers, and Backend Python developers) on the development of an internal customer engagement solution (from design, UI,
development, integration, to run)
• Collaborated with internal and external stakeholders, including Data foundation and governance, Campaign Engagement and operations team, and IT for a business value creation solution through roadmap co-construction and feedback loop,
architectural design and end to end integration
• Experience in managing and delivering products, deployed on AWS cloud infrastructure.
July 2020 - November 2021
KoMED (Kognitive Medizine Assistent)
• Working with 8 different sources of data (including real-time video stream computer vision, video analysis, and protein biomarkers classification), to create a workable and scalable database and finding patterns with AI approaches.
• Designing, Building, and deploying data pipeline to move and transform data (ETL)
• Evaluation and Analysis of medical device data.
HiGHmed (to create three Medical Data Integration Centers (MeDICs) based on a generic and scalable architecture for integrating data from care, research, and external sources)
• Working on an interoperable solution in a medical informatics data pipeline to ingest structured and unstructured data to enable clinical research.
• Being a coder and responsible within a team of data engineers and data scientist for the end-to-end development, testing, and operation of our data science (Feature extraction from Big dataset and Apply ML algorithms) platform
• Working autonomously in a cross-function agile team.
October 2019 - Apirl 2020
Topic: "Predictive Analysis on Rework process in Automotive Assembly line using Deep Learning"
• Analysis and evaluation of defect data of vehicles in manual assembly
• Designed a data science pipeline and neural network for the recognition of error patterns
• Creation of a data-driven machine learning model to predict the feasibility of rework processes within assembly lines
• Testing and validation of the reliability of the learning model for rework locations in vehicle assembly
• Programming language and tools utilized: Python, Spark, Flask, Java, Bigdata analysis,ETL, tableau,Jupiter Notebook
June 2018 - September 2019
Built portal applications for Pepper robot. Which includes (Blog, Video, Demo)
• Recommender system to assist customer shopping. A Content-based method trained to recognize customer dresses and gender as input with the Tensorflow and OpenCV, Predict or recommend based on tags like business, casual, sports.
• Created Chatbot, the robot interacts with customers using a predefined set of topics
• Trained optical character recognition model for printed and handwritten text. Custom translation of the recognized text (using Deepl Translator API and Data Mining using Hadoop)
• API was created for all the Machine learning apps and Data science tools deployed in the cloud (hyper Salers like Amazon AWS and Microsoft Azure)
Involved in the development of a Content Management System for data science tools, with Flutter. So customers can configure machine learning apps and data science tools directly
March 2018 - June 2018
Built Android Application for object recognition and Object measurement
• Worked with Theta S camera(360 degree) to train a Tensor-flow model for Object recognition
• Created image processing algorithm in openCV to generate edges of an object to find the measurement of the objects
June 2016 - July 2017
I was part of Tier-1 AD(Application Development) Team for MetLife Insurance
• Being a programmer analyst, Involved in code changes, Database changes of 3 web applications.
• These applications were developed on Java, JS, and SQL. Agile - Scrum was followed during software development and unit test cases for all the classes