Aditya Pic

About Me

<<<<<<< HEAD I am a graduate student at Brown University concentrating in Computer Science with a focus in Machine Learning and Data Sciences. I have been known to dabble in projects related to data science involving Machine Learning. I love working on complex problem statements. You will find me hiking, taking pictures and playing soccer otherwise. ======= Full-stack Data Scientist at Electrolux HQ in Stockholm, Sweden responsible for key markets in Europe and North America. In my job, I carry passion for architecting Data Science, Data Engineering and associated DevOps pipelining for both cloud and on-premises. Also, I am an active kaggler and contributor to the open source big data projects. Outside work, I am passionate debator and guitar player. >>>>>>> a8d4af4ec66c70cdd43dac30254d13ad31e8052e
Feel free to take a look at my projects, portfolio or contact me below!

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Contact Details

Aditya Kumar Roy
adityakumar.roy94@gmail.com +46738857095

Education

B.Tech in Electronics and Communication Engineering August 2016

Placed in top 5% of the class. GPA: 8.70/10

WES US Equivalent GPA - 3.86/4.0 (Overall) and 3.93/4.0 (Major)

Work

San Francisco

Machine Learning Intern June 2017 - September 2017

Explored techniques like Neural Networks, Supervised Learning, Information Retrieval to find semantic similarity between different issues on GitHub.

Pune

Data Scientist Feb 2016 - August 2016

Applied Machine Learning & Natural Language Processing techniques on unstructured data.

Data Scientist May 2015 - March 2016

Designed Machine Learning algorithms to generate food item taxonomy and hashtags.

Member of Technical Staff June 2014 - May 2015

Worked on multiple tasks in projects related to Data Science.

Skills

  • Data Engineering (Big Data)
  • Machine Learning
  • Deep Learning
  • Natural Language Processing
  • Scala Stack
  • Enterprise Software Development
  • Architecting with Cloud (AWS, Azure, Google Cloud)
  • Project Management

Projects

Food Taxonomy

Classifies Indian food names into different categories like cuisine, meal-type, veg/non-veg etc. Trained on supervised taxonomy data the project assists human labelers. The predictor class is exposed as a micro-service using REST API.

Get In Touch.

Contact me!

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