Vivek Pagadala

Data Scientist

India7 yrs 9 mos experience
Highly Stable

Key Highlights

  • Experienced in building data-driven applications.
  • Proficient in machine learning and data analysis.
  • Strong background in software development and engineering.
Stackforce AI infers this person is a Data Scientist with strong software engineering skills in E-commerce and Tech industries.

Contact

Skills

Core Skills

JavascriptReactMachine LearningNatural Language ProcessingSoftware Development

Other Skills

ReduxNode.jsOAuth2DockerJenkinsTypeScripttf-idfGloVeWord2VecLDAn-gramadd-1 smoothingC++.NETC#

Experience

7 yrs 9 mos
Total Experience
1 yr 8 mos
Average Tenure
--
Current Experience

Meta

Data Scientist

Feb 2022Jun 2024 · 2 yrs 4 mos · Greater Seattle Area

Microsoft

Data Scientist

Apr 2019Oct 2022 · 3 yrs 6 mos · Greater Seattle Area

Flipkart

Software Engineer

Aug 2015Jul 2017 · 1 yr 11 mos · Bangalore

  • ◦ Ad campaign creation: Worked on building an application to enable sellers in Flipkart’s online marketplace to create ad-campaigns, allocate budgets and control the timing and audience of their ads based on user demographics.
  • ◦ Visualizing Ad metrics: Worked on building an application for visualizing advertising metrics such as spends, ad-views, ROI, and awareness uplift. Tech stack: (React, Redux and nodeJS ecosystem).
  • ◦ Authentication and Authorization services: Developed an OAuth2 based authentication service and a dynamically configurable role based authorization service for multiple REST resources.
  • ◦ Dev-ops: Setup a build environment based on Docker & Jenkins along with continuous integration tests. Also worked on migrating a JS codebase to Typescript.
ReactReduxNode.jsOAuth2DockerJenkins+2

Cognitivescale

Internship

Jan 2015Jun 2015 · 5 mos · Hyderabad Area, India

  • ◦ Text search / Word Embeddings: Worked on improving a tf-idf based text search system by using word vectors. Experimented with using GloVe and Word2Vec to improve search query expansion by substituting similar words.
  • ◦ Topic modeling: Experimental topic modeling using LDA (Latent Dirichlet Allocation) on a product reviews dataset.
  • ◦ Language modeling: Worked on integrating custom auto-suggest functionality to search text input using a n-gram based
  • language model with add-1 smoothing.
tf-idfGloVeWord2VecLDAn-gramadd-1 smoothing+2

Morgan stanley

Internship

May 2014Aug 2014 · 3 mos · Mumbai, India

  • ◦ Developed ​compiler plugins​​ in C++ to enhance the .NET platform’s C# compiler to inject user
  • defined bytecode into compiled C# executables.
  • ◦ Enabled the​ runtime profiling​​ of all function calls on a production system.
C++.NETC#Software Development

Education

University of Washington

Master of Science - MS — Data Science

Jan 2017Jan 2019

Birla Institute of Technology and Science, Pilani

B.E. — Computer Science

Jan 2011Jan 2015

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