Marwin Steiner

Data Scientist

https://talent.gravityer.com/marwin-steiner

Researcher | Longhand.dev | Prev. Data Engineer @ Swiss Re

Longhand

Key Strengths

Strong foundational knowledge in Python for quantitative finance and data science applications.
Extensive personal project experience in algorithmic trading, option pricing, and market analysis.
Demonstrated ability to work with large datasets (e.g., Polygon options data) and implement data processing pipelines.
Experience with C++ for performance-critical applications, indicating an understanding of optimization.
Familiarity with machine learning for predictive modeling (e.g., Greyhound racing prediction).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects show a strong interest in quantitative finance and algorithmic trading, which aligns well with roles requiring analytical rigor and problem-solving. The diversity of personal projects indicates self-motivation and a proactive approach to learning and application. However, the lack of team-based projects or professional experience details makes it difficult to fully assess cultural fit beyond individual drive.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback are available.

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Assessing your cultural and operational fit

Projects

polygon-options-puller

March 5, 2026 – Present

Download Polygon (Massive) US options OPRA flat files from S3 and store as compressed Parquet

View Project

signal_processing_labs

February 13, 2026 – Present

Jupyter notebooks for signal processing

View Project

sysls

February 6, 2026 – Present

A systematic multi-asset long-short strategy framework

View Project

pysvi

February 3, 2026 – Present

Stochastic volatility inspired parametrizations of the implied volatility surface in Python!

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ndx-0dte-gamma-imbalance

January 25, 2026 – Present

A gamma volatility arbitrage strategy in the NDX options

View Project

polymarket-bot

January 24, 2026 – Present

An algorithmic trading framework for Polymarket

View Project

greyhound-racing

March 29, 2025 – April 1, 2025

Predicting Greyhound finisher position using ML.

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option-pricer-cpp

March 25, 2025 – March 29, 2025

A C++ port of Artur Sepp's original Numba-accelerated (pure) Python implementation.

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hyperopter

December 3, 2024 – December 19, 2024

A hyperparameter optimization workflow for an algorithmic trading system strategy CI/CD pipeline

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swe-with-llms

December 2, 2024 – December 10, 2024

A software engineering workflow with IDE-integrated LLMs and external validation LLMs.

View Project

Key Strengths

Strong foundational knowledge in Python for quantitative finance and data science applications.
Extensive personal project experience in algorithmic trading, option pricing, and market analysis.
Demonstrated ability to work with large datasets (e.g., Polygon options data) and implement data processing pipelines.
Experience with C++ for performance-critical applications, indicating an understanding of optimization.
Familiarity with machine learning for predictive modeling (e.g., Greyhound racing prediction).

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback are available.

Marwin Steiner

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit