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Иван Силинский
Looking for a job

Иван Силинский

@0005867

I build quantitative forecasting pipelines and execute risk-managed arbitrage across crypto markets and real-time sensor data.

Russian Federation
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What I'm looking for

I'm looking for a quantitative or technical role where I can build and validate data-driven systems, work with real-time data, take ownership of outcomes, and continue growing through challenging applied problems.

I've traded firm capital on a crypto exchange desk, pricing spreads, executing bilateral OTC transactions, and reconciling positions and cash across accounts. I monitored liquidity and spread behaviour daily, then exited the strategy deliberately as structural spread compression eroded its edge.

For ROGII's Wellbore Geology Prediction competition, I built an end-to-end sequential sensor-data forecasting pipeline using particle filtering, beam search, LightGBM, CatBoost, and a Ridge meta-model. I designed guarded reconstruction logic, grouped cross-validation to prevent leakage, and audit checks including SHA-256 fingerprinting.

I've also worked with real-time drilling telemetry at Schlumberger and multi-channel well logs at STS-Geoservice, where analysis informed well stimulation decisions. Most recently, I authored accepted expert mathematics problems for a frontier-model training dataset and am pursuing an MSc in Applied Informatics.

Experience

Work history, roles, and key accomplishments

Education

Degrees, certifications, and relevant coursework

Tomsk State University logoTU

Tomsk State University

Master of Science, Applied Informatics

2026 -

Pursuing an MSc in Applied Informatics with a focus on Computer Vision and Neural Networks.

Irkutsk National Research Technical University logoIU

Irkutsk National Research Technical University

Bachelor of Science, Petroleum Engineering

2019 - 2023

Grade: 4.74/5.0

Activities and societies: Relevant coursework: Statistical Analysis and Design of Experiments, Hydromechanics, Reservoir Physics.

Earned a BSc in Petroleum Engineering with a weighted average of 4.74/5.0, with Mathematics and Physics graded Excellent.

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