プロフィール詳細

プロジェクトを作成

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Shaurya U.に依頼

India

Data Scientist | Mentor | Problem Setter Expert | Expert in Python, SQL, EDA, TimeSeries and NLP

プロフィール概要

Experience in working with burgeoning companies of InMobi(Glance), Tata 1mg (e-pharmacy) and epiFi (neo banking - fintech). I have worked on a recommendation engine, NLP, TimeSeries, Machine Learning Statistical, and many other data science problems end to end to production. In academics also, I hold a good track record of consistent 8+ cgpa out of 10 throughout all semesters. I have a bias for action, solution-oriented, and have a good track record in communicating with stakeholders and establishing credibility. My role involves deciphering heaps of data, analyzing it, churning out meaningful insights from the data, and assisting stakeholders to make data-driven decisions. Also awarded with titled of Top 10 Active Data Scientist in India on LinkedIn. LinkedIn: https://www.linkedin.com/in/shaurya-uppal/

専門分野

• ★ Data Science
• ★ Trend Analysis
• ★ SQL
• ☆ Data Analysis
• ☆ Data Processing
• ☆ Data Exploration
• ☆ Data Visualization
• ☆ Data Manipulation
• ☆ Machine Learning
• ☆ Data Cleaning
• ☆ Natural Language Processing
• ☆ Data-Driven Decision Making

サービス

• Writing
• Research
• Data & AI

Writing Technical Writing, Copywriting

Research Gray Literature Search, Systematic Literature Review, Secondary Data Collection

Data & AI Statistical Analysis, Algorithm Design-Non ML, Data Visualization

職務経験

Lead Data Scientist

Siam Makro (CP Axtra)

6月 2023 - 現在

Data Scientist

epiFi - Neobanking (FinTech)

5月 2020 - 現在

Sr. Data Scientist

InMobi

7月 2021 - 6月 2023

Data Scientist

1mg

2月 2019 - 5月 2020

Data Scientist - Mentor and Problem Setter

InterviewBit (e-learning)

12月 2018 - 5月 2020

学歴

MS Computer Science

Georgia College - United States

1月 2023 - 現在

B.Tech with Honors (CGPA 8.6) (Computer Science)

Jaypee Institute of Information Technology

4月 2015 - 2月 2019

認定資格

• 認定資格の詳細は未入力です。

出版物

CONFERENCE PAPER

(2020). Comparative Analysis for {KeyTerms} Extraction Methods for Personalized Search Engines . {IEEE}

(2019). Pairwise Reviews Ranking and Classification for Medicine E-Commerce Application . {IEEE}