Navya Arora

Product Manager

London, United Kingdom0 mo experience

Key Highlights

  • Expert in Machine Learning and Data Analysis
  • Developed management systems for tech applications
  • Automated anomaly detection for major e-commerce platform
Stackforce AI infers this person is a Data Science and Machine Learning professional with experience in Fintech and E-commerce.

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Skills

Core Skills

Machine LearningProblem SolvingDatabase DesignAnomaly DetectionData Analysis

Other Skills

C++Convolutional Neural Networks (CNN)Data StructuresDeep LearningKibanaManagement SystemsNumPyProgrammingPythonResearchSciPySentiment AnalysisStatistical Analysis

Experience

0 mo
Total Experience
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Average Tenure
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Current Experience

Alphagrep investment management

Quantitative Researcher

Jul 2023Present · 2 yrs 10 mos · London Area, United Kingdom · On-site

  • High frequency market making for NSE index and stock options.
PythonData StructuresMachine LearningProblem Solving

Graviton research capital llp

Quantitative Research Intern

Jun 2023Jul 2023 · 1 mo · Gurugram, Haryana, India · On-site

The d. e. shaw group

DESIS Acsend Educare Fellow

Oct 2021Apr 2022 · 6 mos

  • Database design project:
  • Developed a management system for a food delivery app to store, manage and explore different restaurants, make orders, and contain their information, a delivery system supporting different payments and discount options.
  • Designed an ER model and translated the model to the relational schema for a management system of the same.
Database DesignManagement Systems

Flipkart

Flipkart Intern

Jun 2021Aug 2021 · 2 mos

  • Automating the anomaly detection process for Flipkart Credit Card issuing system by deploying Kibana, such that information is retrieved automatically after a window period of every one hour and in case of an anomaly in any of the parameters, the team is notified
Anomaly DetectionKibana

Ucl

Summer Research Intern

May 2021Jul 2021 · 2 mos

  • 1. Measured the interaction between the flow of sentiments expressed through Twitter & the dynamics of the stock market prices from the Jaccard similarity index & correlation values between them using sklearn and SciPy libs
  • 2. Analyzed how a change in sentiment index of one financial institution affected its own value, and how other financial institutions are affected by it using the Minimum Spanning Tree of the distance between their correlation values
  • 3. Investigated how the given time-series is more informative than the null hypothesis by calculating the Z-score of correlation values for 244 days data of stocks and sentiment index of 22 different airline companies.
Data AnalysisSentiment AnalysisStatistical AnalysisSciPy

Education

Indian Institute of Technology, Delhi

Bachelor of Technology - B. Tech — Mathematics and Computer Science

Jul 2019Jun 2023

Rukmini Devi Public School

High School — Science & Mathematics

Apr 2005Mar 2019

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