ARPAN NANDI

AI Researcher

Gurugram, Haryana, India5 yrs 2 mos experience

Key Highlights

Expert in algorithmic trading strategies development.
Strong background in machine learning and data analysis.
Proven ability to automate complex data processes.

Stackforce AI infers this person is a Quantitative Analyst with expertise in algorithmic trading and data management.

Contact

Skills

Core Skills

Data ManagementAlgorithm Development

Other Skills

Academic ResearchAdobe PhotoshopCC++Cascading Style Sheets (CSS)Computer NetworkingData CatalogingData Lineage ProcessingDatabase Management System (DBMS)Deep LearningFlaskFront-end DevelopmentFull-Stack DevelopmentGDScriptGame Development

About

I am a Quant researcher, and I have been developing and running algorithmic medium frequency trading strategies in Index and commodity futures across exchanges for more than a year. My work has been revolving around deep diving into data, in search of valuable insights, aligned with the requirements of the existing portfolio and developing strategies around those insights. I have majorly worked on Index futures of different exchanges (usa, brazil, europe, japan, India etc.), commodities futures in cme and mcx, and Indian stock futures. Being a computer science graduate, my understanding of algorithms, and background in machine learning provides an extra edge of time and accuracy in constant research. I also bring a healthy combination of patience, passion, and enthusiasm for learning. I love taking strong decisions, and full responsibility for those. I love brewing new ideas, and to listen to many more. Feel free to connect, let's cultivate new ideas together !

Experience

26milescapital

Quant Researcher

Aug 2023 – Present · 2 yrs 7 mos · Gurugram, Haryana, India · On-site

Workspot, inc

Software Developer

May 2022 – Jul 2022 · 2 mos · Hyderabad, Telangana, India

Project : Developing a data cataloging and metadata management tool for Enterprise Data Platform.
Metadata modelling for the organisation’s data in data warehouse, to increase accessibility of data, across teams.
Implemented algorithms to process the complete data lineage of every object in the warehouse and incrementally update the
processed information within 10-20 minutes (depending on depth and branching), and versionizing the same.
This automated 100% of the technical Impact analysis, significantly enhancing the efficiency and usability of the EDP.
Project : A chatbot for self service analytics (free form questions - convert to SQL - fetch from Data platform)
Schema specific rule based and regex based parsing in backend, to generate simple SQL statements from free text.
Democratises access to data by answering frequent ad-hoc questions. Also response time is reduced to around 8-10 seconds,
helping business decisions and insights to be data driven. Also provides abstraction to the original data.