About
On the record
I am a full-stack bayesian data scientist specializing in forecasting, financial modeling and modeling of uncertainty. My work goes beyond research: I make end-to-end data solutions from research and modeling to opening data pipelines, automating dataflow, deploying the trained models and creating a dashboard for the end-user. I am an ex-graphic designer - my data looks good. I studied at Aalto University majoring in economics focusing mainly on macro and econometrics and minoring in quantitative methods, i.e. more econometrics. I love what I do. Technologies I use- Python - Rust - Stan - SQL - R - Django - Azure - Databricks - Docker - Linux - Power BI - Dune analytics My current research and work has from 2020 revolved around blockchain related economics and technology. Here are some previous and on-going projects I have a lot of experince on- Macroeconomics-driven cryptocurrency valuation modeling - Market-making of stablecoins in decentralized finance exchanges - Volatility modeling of cryptocurrencies, derivatives and hedging - Portfolio modeling - Zero-knowledge Machine Learning - Automation of consumer loan pricing and credit risk decisions: everything from research to production code Statistical & ML Armory- bayesian regressions - bayesian time series - bayesian networks - models with quasi-experimental methods - tree-based models such as extreme gradient boosting - heavy user of scipy minimize - packages: scipy, statsmodels, pystan, pymc, pygam, xgboost, torch, pomegranate Books I've read:
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