Group Manager - AI
Signify

www.signify.com
Eindhoven, Netherlands
April 2020 - Present

Leading a data science research team to create data driven services across different business sectors. Below is a summary of the different activities I am involved in:

• Building Data & AI strategy to differentiate our products, specially in the domain of Agriculture and Home lighting.
• Technically leading a team of data scientists to deliver value from AI.
• Keeping my hands dirty by implementing a serverless data analytics pipeline on AWS using AWS Lambda, Glue, and QuickSight to democratize data analytics for vertical farming light recipe researchers.
• Architecting implementation of next generation ML/AI solutions on the cloud with a strong focus on MLOps and Explainability.

ML Engineer
ASML

www.asml.com
Veldhoven, Netherlands
October 2018 - March 2020

Working in the Development and Engineering team to build, productize, and scale machine learning models for the current and new generation of Lithography machine (EUV & DUV). Below is a summary of different projects I have been involved in:

• Machine Learning Pipeline: Designing end to end scalable machine learning pipeline for production end using technologies like Kubeflow, Sklearn, XGBoost, and Google Cloud Platform.
• Streaming Data Pipeline: Implemented a streaming back end for high throughput data using: Kafka, Docker, Kubernetes, and Grafana.

Scientist/ Big Data Engineer
Philips Lighting Research (now Signify)

http://www.philips.com/research
Eindhoven, Netherlands
August 2016 - September 2018

Working in Philips Lighting Research to design, develop, and implement production-ready big data pipelines with advanced analytics or machine learning models. To do so, I work with the following layers and use the following technologies:

• Programming Language: Java, Python, Scala
• Web Framework: Flask
• Big Data Processing: Spark
• Machine Learning Libraries: scikit-learn, MLlib, Spark ML, Keras
• Data Access & Integration: Kafka, Hive, ElasticSearch
• Orchestration & Workflow Management: Airflow
• Data Visualization or Analytics: Kibana, Superset
• Cloud Platform: Amazon Web Services

Data Scientist (Intern)
ING

http://www.ingwb.com/
Amsterdam, Netherlands
January 2016 - June 2016

Working with the Commercial Banking Advanced Analytics team to implement a dynamic real-time data pipeline framework to enable efficient rapid data pipeline deployment. In addition, I have achieved the followings:

• Design and implement data pipelines for end to end processing of data using different Hadoop oriented technologies
• Write scripts in Python and R to transform, clean, and analyze data
• Process and warehouse streaming datasets using Spark Streaming
• Write REST based service APIs in Python and Java to consume and produce data over a RESTful Web Service
• Implement a data pipeline to extract relevant data from Twitter, analyze, and then load the summary on a RDBMS
• Develop a Java web application to visualize and create dynamic reports on the analytics data processed by the Twitter pipeline. The idea behind this data pipeline and application was to enable ING better understand customers on Twitter

Business & Product Development Manager
Gonona Technologies Limited

www.gonona.net
Dhaka, Bangladesh
June 2012 - February 2014

Collaborate with the marketing department to understand market demand and coordinate with the technical team to define product release requirements to realize those market demands.

• Document new business and product concepts
• Analyze the technical and market feasibility of new product plans
• Create comprehensive business plans and marketing plans
• Represented the organization in CeBIT and other trade exhibits