Kiril Sarvanau

Applied Mathematics graduate with strong foundations in probability, statistics, and algorithmic reasoning.

Competitive participant in mathematical and programming challenges. Experienced in designing and testing systematic models using statistical analysis and machine learning. Focused on market microstructure and low-latency price dynamics, aiming to contribute to high-performance trading research.

AI Training Specialist & ML Evaluator (Freelance) at Alignerr (2025-09 – Present)

Evaluate and benchmark Large Language Model (LLM) performance on complex code implementation tasks and refine model reasoning through RLHF.

• Evaluate and benchmark Large Language Model (LLM) performance on complex code implementation tasks, focusing on feature integration within broad GitHub repositories
• Refine model reasoning and QA capabilities through RLHF, developing high-quality YAML-based training scenarios
• Perform multi-modal data verification, transcribing and structuring specialized aerospace communications to improve domain-specific AI precision

Quantitative Analyst Intern at InData Labs (2024-06 – 2024-08)

Improved risk-adjusted returns through volatility forecasting models and market analytics.

• Improved risk-adjusted returns by 7% by engineering and backtesting a Scikit-learn model for market volatility forecasting
• Monitored and analyzed large-scale historical datasets of global equity and FX markets using Python (Pandas, NumPy) to investigate anomalies in data and trading behavior
• Designed and developed intuitive tools and interactive dashboards (Matplotlib, Seaborn) for visualizing market dynamics and risk exposures, leading to the adoption of a new risk parameter

Bachelor of Science in Applied Mathematics – University of Twente (2022-09 – 2025-07)

Exchange Program in Computer Science – Warsaw University of Technology (2024-10 – 2025-02)