Rupam Kumar Dubey

Operations Associate

Mumbai, Maharashtra, India4 yrs 10 mos experience

Most Likely To Switch

Key Highlights

Strong analytical skills in financial markets.
Proficient in machine learning and data analysis.
Experience in algorithmic trading and recommendation systems.

Stackforce AI infers this person is a Fintech professional with expertise in machine learning and financial analysis.

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Skills

Core Skills

Machine LearningData AnalysisBusiness ValuationRecommendation Systems

Other Skills

Algorithmic ModelsAlgorithmsC (Programming Language)C++Capital MarketsCollaborative FilteringContent-Based RecommendationData ExtractionData ScienceDeep LearningDerivativesFinancial MarketsFixed Income StrategiesInterest Rate DerivativesMicrosoft Excel

About

Currently working with an investment bank. I've cultivated a strong work ethic since a young age, driven by curiosity for learning. Deeply passionate about financial markets and the ever-evolving landscape of global economics. Thrive on challenging the status quo, believes in reading and critical thinking.

Experience

Nomura

Associate

Apr 2024 – Present · 1 yr 11 mos · Mumbai, Maharashtra, India · On-site

Global Markets - FO

Credit suisse

Market Risk Management - Fixed Income

Jul 2022 – Apr 2024 · 1 yr 9 mos · Mumbai, Maharashtra, India

Nri (nomura research institute)

Management Consultant

Jan 2022 – Mar 2022 · 2 mos

Iit kharagpur quiz club

Governor

Apr 2021 – Feb 2022 · 10 mos

Credit suisse

Summer Intern- Equities Prime Services

Apr 2021 – Jun 2021 · 2 mos · Mumbai, Maharashtra, India

Pre-Placement offer for displaying high performer attributes

Indian school of business

Quantitative Research Intern

May 2019 – Jul 2019 · 2 mos · Hyderabad, Telangana, India

Machine Learning:
Examined the impact of transaction failures on the working of a biometric enabled payment system introduced in India to facilitate banking by the poor using Machine Learning Algorithm
Trading Strategies:
Developed Algorithmic Models to execute and back-test trading strategies and achieve returns of 14.56%, 16.37%, 10.98% on implementing Pitroski F-Score) strategies in Indian Markets
Extracted financial data from NSE, Prowessdx, Bloomberg LP by automating the web browser using Selenium, Beautiful Soup
Valuation:
Certified for completing a study on Business Valuation (WACC and APV) and assessed Busines cases of HBS and INSEAD

Machine LearningAlgorithmic ModelsData ExtractionBusiness ValuationData Analysis

Indian institute of technology, kharagpur

2 roles

Research Paper | Machine learning to analyse ratings | Prof Swagato Chatterjee

Feb 2019 – May 2019 · 3 mos

We analysed consumer decision-making involving pre-purchase information and post-purchase outcomes. In order to extract data for the project of various E-commerce websites we used Beautiful soup. After collecting the data we applied SVR(linear Kernel) Xgboost and Random Forrest models in order to get Relative Importance of various pre and post purchase variables.

Data ExtractionMachine LearningSVRXgboostRandom Forest

Recommendation Engine | Prof Swagato Chatterjee

Nov 2018 – Feb 2019 · 3 mos

Developed a web based recommendation engine by making use of user based collaborative filtering (CF) engine and combining content based recommendation results along with it. The system makes use of numerical ratings of similar items between the active user and other users of the system to assess the similarity between users’ profiles to predict recommendations of unseen items to active user. The system makes use of cosine similarity correlation to evaluate the similarity between users.

Recommendation EngineCollaborative FilteringContent-Based RecommendationRecommendation Systems