Olgierd is available for hire
Hire OlgierdOlgierd Michalak
Verified Expert in Engineering
Data Science and BI Developer
Warsaw, Poland
Toptal member since June 17, 2020
Bio
Olgierd specializes in data engineering, AI engineering, and data science, mostly on Google Cloud Platform. Well-versed in business and financial concepts, he can build data products and analytics solutions that will fit well with the business strategy. Faced with complexity, uncertainty, risk, volatility, and ambiguity, he turns to Agile. Recently, Olgierd worked extensively on data engineering jobs in Google Cloud.
Portfolio
Self-employed
Management Accounting, Financial Data Analytics, Financial Market Data, Trading...
Accenture
Banking & Finance, Agile Business Analysis, Financial Markets, Finance
Goldman Sachs
Business Intelligence (BI), Data Analysis, Data Reporting, SQL...
Experience
- Business Intelligence (BI) - 20 years
- Data Engineering - 20 years
- Python - 20 years
- Financial Markets - 20 years
- Data Science - 15 years
- Google Cloud Platform (GCP) - 7 years
Preferred Environment
Financial Markets, Banking & Finance, Data Science, Google Cloud Platform (GCP), Machine Learning, Business Intelligence (BI), Analytics, Python, Finance
The most amazing...
...project that I worked on was with ML models that used economic and financial data to support my client's investment decisions.
Work Experience
Data Engineering, Analytics, and Science Consultant
2018 - PRESENT
Self-employed
- Architected, engineered, and operationalized robust, end-to-end data pipelines and machine learning infrastructure on Google Cloud Platform to build enterprise-tier data products.
- Delivered cloud data solutions, data engineering tasks, and scalable data analytics systems for blue-chip organizations, including GSK, BMW, Nestle, H&M, and JLL.
- Orchestrated production-grade machine learning pipelines utilizing Vertex AI and PySpark (Dataproc) to optimize automated model training, operational monitoring, and business-critical predictive execution.
- Designed and deployed high-performance ETL/ELT pipelines streaming structured and unstructured datasets into BigQuery, accelerating internal query speed and ad-hoc client visualization capacities.
- Analyzed real-time electricity market fluctuations and engineered automated back-testing architectures for advanced trading strategies for Kyoto.
- Conducted critical quantitative market research and robust strategy back-testing workflows using Python libraries for premium algorithmic financial entities, including Two Sigma and some Toptal clients.
Technologies: Management Accounting, Financial Data Analytics, Financial Market Data, Trading, Financial Reporting, Data Analysis, Data Reporting, SQL, Time Series Analysis, Quantitative Finance, Banking & Finance, Agile Business Analysis, Data Science, Google BigQuery, Predictive Modeling, Machine Learning, Gradient Boosted Trees, Pandas, Analytics, Python, NumPy, Data Visualization, Statistics, Scikit-learn, Financial Markets, SciPy, StatsModels, Matplotlib, Data Mining, Quantitative Analysis, Finance, Business Intelligence (BI), Linear Regression, Logistic Regression, Dimensional Modeling, ETL, Financial Analysis, Financial Modeling, Data Engineering, Google AI Platform, Google Cloud ML, Artificial Intelligence (AI), Google Cloud Platform (GCP)
Consultant
2017 - 2017
Accenture
- Formulated deep architectural technical blueprints from "As-Is" infrastructure states to target "To-Be" enterprise landscapes to implement risk management and system stress-testing applications in banking for Nordea Bank.
- Delivered high-value architectural structural blueprints, evaluating enterprise liquidity metrics and liquidity management controls.
- Mapped strategic operational requirements and structural milestones to advance legacy database configurations toward modernized analytical environments for Raiffeisen Bank.
Technologies: Banking & Finance, Agile Business Analysis, Financial Markets, Finance
Risk Analytics Associate
2015 - 2016
Goldman Sachs
- Built interactive, production-level Tableau tracking models and operational dashboards to deliver complex risk intelligence insights to localized and global risk assessment groups.
- Engineered high-velocity risk data processing routines and computational algorithms using PySpark across large-scale datasets.
- Delivered advanced, data-driven technical presentations detailing cutting-edge data science methodologies and implementation strategies to executive leadership stakeholders.
Technologies: Business Intelligence (BI), Data Analysis, Data Reporting, SQL, Banking & Finance, Data Science, Predictive Modeling, Machine Learning, Gradient Boosted Trees, Pandas, Analytics, Python, NumPy, Data Visualization, Statistics, Scikit-learn, SciPy, Matplotlib, Data Mining, Quantitative Analysis, Agile Business Analysis, Finance, Logistic Regression, Dimensional Modeling, Financial Reporting, Data Engineering
Business Intelligence Consultant
2014 - 2015
Self-employed
- Directed technical consulting initiatives to analyze client data ecosystems and implement scalable data engineering, pipeline automation, and regulatory reporting systems.
- Collaborated closely with Capgemini Financial Services to architect and construct a highly successful PoC analytical back-end framework for Lloyds Banking Group.
- Designed, structured, and led advanced visual analytics workshops and Tableau software engineering training modules for senior enterprise technical consultants.
Technologies: Financial Data Analytics, Business Intelligence (BI), Financial Reporting, Data Analysis, Data Reporting, SQL, Banking & Finance, Agile Business Analysis, Management Accounting, Predictive Modeling, Machine Learning, Gradient Boosted Trees, Pandas, Analytics, NumPy, Data Visualization, Statistics, Scikit-learn, Financial Analysis, SciPy, StatsModels, Matplotlib, Linear Regression, Logistic Regression, Quantitative Analysis, Finance, Data Science, Financial Markets, Python, Dimensional Modeling, ETL, Financial Modeling, Financial Market Data, Data Engineering
Business Intelligence Architect
2011 - 2013
Soft Computer Consultants
- Evaluated several BI technologies and recommended what best suited the company's strategy.
- Designed data warehouse dimensional models.
- Prepared analyses and dashboards in Tableau.
Technologies: Business Intelligence (BI), Financial Reporting, Data Analysis, Data Reporting, ETL, SQL, Analytics, Python, Data Visualization, Statistics, Dimensional Modeling, Quantitative Analysis, Agile Business Analysis, Finance, Data Science, Financial Markets, Management Accounting, Predictive Modeling, Machine Learning, Logistic Regression, Financial Analysis, Financial Modeling, Data Engineering
Reporting and Data Warehouse Analyst
2008 - 2010
Toyota Bank Polska
- Prepared over 200 management and operational reports for the bank departments, including accounting, treasury, marketing, sales, and debt collections.
- Built data warehouse data models with management-oriented data marts for ad-hoc reporting and analyses.
- Helped coordinate continuous improvement (Kaizen) activities.
Technologies: Financial Data Analytics, Business Intelligence (BI), Financial Reporting, Data Analysis, Data Reporting, ETL, SQL, Banking & Finance, Management Accounting, Financial Modeling, Analytics, Python, Data Visualization, Statistics, Financial Analysis, Dimensional Modeling, Data Mining, Linear Regression, Logistic Regression, Quantitative Analysis, Agile Business Analysis, Finance, Data Science, Financial Markets, Predictive Modeling, Machine Learning, Financial Market Data, Data Engineering
Business Intelligence Consultant
2004 - 2007
Freelance
- Performed business analysis and helped create a project plan for a financial data warehouse (or KBC).
- Led the business analysis for the data warehouse to support the monitoring and control of the state-wide electric grid (for PSE - electricity transmission system operator).
- Helped perform business analysis for a data warehouse (for Vattenfall).
- Helped build and test a data warehouse (for TPSA, now Orange).
Technologies: Financial Data Analytics, Business Intelligence (BI), Financial Reporting, Data Analysis, Data Reporting, ETL, SQL, Banking & Finance, Agile Business Analysis, Management Accounting, Python, Financial Analysis, Dimensional Modeling, Quantitative Analysis, Finance, Data Science, Financial Markets, Statistics, Data Visualization, Financial Modeling, Analytics, Data Engineering
Programmer | Business Analyst
2000 - 2003
Soft Computer Consultants
- Created a PoC solution of a BPM using dynamic HTML (Ajax did not exist then) and PHP.
- Programmed parts of the system in JavaScript and Java.
- Synchronized MS Projects with the company's internal project management system.
Technologies: Business Intelligence (BI), Financial Reporting, Data Reporting, SQL, Quantitative Analysis, Agile Business Analysis, Data Analysis, Management Accounting, Python, Data Visualization, Dimensional Modeling, ETL, Financial Analysis, Financial Modeling, Analytics, Data Engineering
Programmer | Business Analyst
1997 - 1999
American Management Systems
- Helped build a PoC solution for the new telecom platform.
- Programmed the CRM modules.
- Created ETL procedures to migrate the customer data.
Technologies: Business Intelligence (BI), Data Analysis, ETL, SQL, Quantitative Analysis, Analytics, Data Engineering
Programmer
1996 - 1997
SoftSystem
- Documented business requirements.
- Programmed parts of the accounting application.
- Implemented automated software builds, integration, and testing.
Technologies: Management Accounting, Financial Reporting, SQL, Data Analysis, Financial Analysis, Financial Modeling, Analytics, Data Engineering
Experience
Predicting Loan Defaults
https://github.com/olgierdmic/Predicting-Loan-DefaultsThis repository is about a structured approach to building predictive models for binary classification.
Built a machine learning model that can predict a loan default. The most common data science process steps have been followed, from preparing the data, building a machine learning model, evaluating it, and reporting the results.
Built a machine learning model that can predict a loan default. The most common data science process steps have been followed, from preparing the data, building a machine learning model, evaluating it, and reporting the results.
Option Pricing with Analytical Formulas and MC Simulations
https://github.com/olgierdmic/Quant-FinanceThe notebook shows how to compute the derivative prices using both analytical and stochastic methods. Besides plain vanilla options, calculated with the Black-Scholes-Merton formula, the Asian options' prices are computed with MC simulations.
Financial Risks Management
https://github.com/olgierdmic/Quant-FinanceThe notebooks show the valuations of Asian options using analytical and MC simulations and the computations of the probability-of-default metrics used for the regulatory credit risk management in banking, including the Merton structural model, the Black-Cox model, and the Monte Carlo simulation approach.
Education
1990 - 1995
Master of Science Degree in Applied Physics and Math
Warsaw University of Technology - Warsaw, Poland
Certifications
FEBRUARY 2023 - FEBRUARY 2025
Professional Data Engineer
Google Cloud
JANUARY 2020 - PRESENT
Scrum Product Owner Accredited Certification
Scrum Institute
JANUARY 2018 - PRESENT
Certificate in Quantitative Finance
CQF Institute
JULY 2007 - PRESENT
CIMA Diploma in Management Accounting
CIMA (ref. nr 1-1UVWVL)
JULY 2007 - JULY 2012
PMI Certified Associate in Project Management
PMI (CAPM Number 480759)
Skills
Libraries/APIs
Scikit-learn, Pandas, NumPy, SciPy, Matplotlib
Tools
Google AI Platform, StatsModels
Languages
SQL, Python
Paradigms
Business Intelligence (BI), ETL, Dimensional Modeling, Agile Business Analysis
Platforms
Google Cloud Platform (GCP)
Industry Expertise
Banking & Finance
Other
Data Science, Trading, Machine Learning, Data Analysis, Financial Analysis, Financial Modeling, Financial Markets, Data Visualization, Data Reporting, Financial Reporting, Predictive Modeling, Google BigQuery, Statistics, Data Mining, Time Series Analysis, Linear Regression, Logistic Regression, Gradient Boosted Trees, Quantitative Finance, Financial Market Data, Financial Data Analytics, Quantitative Analysis, Analytics, Data Engineering, Google Cloud ML, Management Accounting, Finance, Artificial Intelligence (AI)
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