Sean Gupta

Lead ML Engineer

Singapore, Singapore6 yrs experience

AI EnabledAI ML Practitioner

Key Highlights

5+ years in data science and quantitative research
Expert in machine learning for financial markets
Applied data science in healthcare and legal sectors

Stackforce AI infers this person is a Fintech expert specializing in quantitative research and machine learning applications.

Contact

Skills

Core Skills

TradingQuantitative ResearchMachine LearningConsultingData ScienceResearchEducationMathematicsProject Management

Other Skills

Amazon Web Services (AWS)Artificial Intelligence (AI)Big DataCryptoCryptocurrencyData AnalysisDeep LearningDigital AssetsGitInternational ExperienceLinuxMapleMatlabMicrosoft ExcelNatural Language Processing (NLP)

About

With 5+ years of experience in data science and quantitative research, I specialise in leveraging machine learning and quantitative techniques to drive innovation and profitability in financial markets. I have led the development and implementation of advanced trading strategies in delta one crypto markets, focusing on market microstructure and predictive models. My strong foundation in mathematics and machine learning is supported by postgraduate degrees from UCL and Cambridge. Beyond finance, I have successfully applied my data science expertise to the healthcare and legal sectors. I am passionate about continuous learning and thrive in collaborative environments. I am eager to adopt new technologies and methodologies to deliver cutting-edge solutions.

Experience

Blocktech

Quantitative Developer

Jul 2024 – Present · 1 yr 8 mos · Singapore · On-site

Researching and developing high frequency delta 1 crypto trading strategies
Scaling trading systems to enable expansion into multiple exchanges and markets

TradingLinuxCryptoBig DataCryptocurrencySQL+6

Analytico trading

2 roles

Senior Quantitative Researcher

Promoted

Mar 2023 – Oct 2023 · 7 mos · Remote

Drove profitability for an algorithmic crypto market maker (Spot / Futures, top-10 on Binance by volume)
Mentored colleagues in implementing and monitoring machine learning algorithms
Guided development team in productionising machine learning models
Led research into reinforcement-learning based trading

TradingAmazon Web Services (AWS)Deep LearningLinuxArtificial Intelligence (AI)Machine Learning+10

Quantitative Researcher

Aug 2021 – Mar 2023 · 1 yr 7 mos · Remote

Introduced first-ever application of machine learning into the business; researched and productionised ML pricing models in Python in an AWS environment; high predictive accuracy allowed for novel trading strategies
Developed new trading strategies based on market microstructure
Collaborated cross-functionally with development, data engineering and operations teams

TradingAmazon Web Services (AWS)Deep LearningLinuxArtificial Intelligence (AI)Machine Learning+10

Chambers and partners

Data Scientist

Mar 2021 – Aug 2021 · 5 mos · London, England, United Kingdom

Worked directly with C-Suite of private equity backed legal research firm
Segmented customers to evolve product offering and deliver targeted marketing campaigns
Improved pricing strategy to drive revenue growth across all product categories

ConsultingArtificial Intelligence (AI)Machine LearningSoftware DevelopmentPricing AnalysisStatistical Modeling+2

Sensyne health

Data Scientist

Jun 2020 – Feb 2021 · 8 mos · London, England, United Kingdom

Worked in large commercial research project at clinical AI company, using Python
Applied and researched data-driven methods to answer clinical questions about real-world NHS data from electronic healthcare records (EHRs)
Implemented predictive analytics via supervised and unsupervised learning including robustness analysis and whitebox models to interpret complex results
Implemented statistical methodologies including survival and enrichment analysis
Interviewed and conducted technical tests for potential new employees

StatisticsDeep LearningLinuxArtificial Intelligence (AI)Machine LearningBig Data+4

The london school of economics and political science (lse)

Research Assistant

Oct 2019 – Jun 2020 · 8 mos · London, United Kingdom

Analysed domestic abuse and criminal record databases to predict future recidivism in domestic abuse cases (predictive policing) using random forests, boosted models and logistic regression in R
Predicted knife crime hotspots in London from spatial and criminological data
Cleaned and pre-processed data
Developed efficient algorithms to generate criminal history information from raw data
Assessed predictor importance and robustness of results in highly imbalanced dataset

RStatisticsArtificial Intelligence (AI)Machine LearningResearchBig Data+3