09/23/2026 updated
100 % available
Quantitative analyst: Python data pipelines, API collectors, backtesting after costs
Vilnius, Lithuania
Only remote
MSc in Economics and Business, FinanceAbout me
I build Python that collects market and web data unattended, and I test whether an idea still works after costs. MSc in Finance, four public studies with code on GitHub, collectors that processed millions of records. I agree the scope in writing first and say plainly when something fails.
Application Programming Interfaces (APIs)Data AnalysisData ProfilingPython (Programming Language)BacktestingData PipelinePipeline Reporting
Python Data Pipelines
Development of Python pipelines using pandas, NumPy, Matplotlib, asyncio and requests for collecting market and web data unattended, including streaming and REST collectors with automatic reconnects, crash recovery, JSONL/SQLite storage and daily integrity checks.
Backtesting and Strategy Validation
Rigorous backtesting and strategy validation with commissions, spread, slippage and queue position accounted for first; use of held-out samples, bootstrap confidence intervals, required sample size and power analysis to avoid overfitting.
SQL Reporting and Data Analysis
Advanced SQL skills covering CTEs, window functions and pivots across SQLite and PostgreSQL; reproduction of analytical results independently in SQL and transformation of manual Excel reports into automated, reproducible scripts.
REST and Streaming API Integration
Integration of REST and streaming market-data APIs with handling of rate limits, retries, certificate authentication and scheduled jobs, applied to betting exchange and crypto exchange endpoints.
Statistical Methods
Application of hypothesis testing, bootstrap confidence intervals, logistic regression and calibration, power analysis and out-of-sample validation to quantitative research problems.
Finance and Market Microstructure
Knowledge of exchange microstructure, execution costs, effective and realised spread, adverse selection, odds and bookmaker margin, futures funding, portfolio backtests, financial statement analysis and credit assessment.
Data Cleaning and Analysis Reporting
Transformation of messy CSV and API data into usable datasets, accompanied by written reports explaining what the numbers do and do not show.
Excel Automation
Conversion of manual Excel-based reports into Python and SQL scripts that run themselves, with tests and reproducible output; advanced Excel skills including complex formulas and data management.
Development of Python pipelines using pandas, NumPy, Matplotlib, asyncio and requests for collecting market and web data unattended, including streaming and REST collectors with automatic reconnects, crash recovery, JSONL/SQLite storage and daily integrity checks.
Backtesting and Strategy Validation
Rigorous backtesting and strategy validation with commissions, spread, slippage and queue position accounted for first; use of held-out samples, bootstrap confidence intervals, required sample size and power analysis to avoid overfitting.
SQL Reporting and Data Analysis
Advanced SQL skills covering CTEs, window functions and pivots across SQLite and PostgreSQL; reproduction of analytical results independently in SQL and transformation of manual Excel reports into automated, reproducible scripts.
REST and Streaming API Integration
Integration of REST and streaming market-data APIs with handling of rate limits, retries, certificate authentication and scheduled jobs, applied to betting exchange and crypto exchange endpoints.
Statistical Methods
Application of hypothesis testing, bootstrap confidence intervals, logistic regression and calibration, power analysis and out-of-sample validation to quantitative research problems.
Finance and Market Microstructure
Knowledge of exchange microstructure, execution costs, effective and realised spread, adverse selection, odds and bookmaker margin, futures funding, portfolio backtests, financial statement analysis and credit assessment.
Data Cleaning and Analysis Reporting
Transformation of messy CSV and API data into usable datasets, accompanied by written reports explaining what the numbers do and do not show.
Excel Automation
Conversion of manual Excel-based reports into Python and SQL scripts that run themselves, with tests and reproducible output; advanced Excel skills including complex formulas and data management.
Experience
Professional experience0 - 5 years
Freelancer since2026
Languages
EnglishGoodRussianNative speakerLithuanianBasic knowledge
Project history
Built Python collectors on betting exchange streaming and REST APIs for four sports covering order books, traded volume, in-play state and starting-price auction data with automatic recovery after failures. Processed 2.8 million order-book snapshots and reconstructed 1.6 million trades from cumulative volume to measure execution costs including effective spread, realised spread and adverse selection. Tested and closed more than 15 strategy hypotheses with written pre-registration, held-out samples and power analysis; published four studies with code.
Owned and operated a vending network of about 300 machines and later barbershops across Karaganda, Kazakhstan and Vilnius, Lithuania. Responsible for profit and loss in two countries including pricing, purchasing, staff, marketing, tax and licensing. Planned restocking routes, reconciled cash collections and reported results to a business partner.
Sold lifting equipment and managed client accounts and receivables.