Alexander Demachev

CEO

Dubai, United Arab Emirates10 yrs 3 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Led a quant team achieving significant trading returns.
Developed innovative LLM-driven trading strategies.
Expert in statistical modeling and financial analysis.

Stackforce AI infers this person is a Fintech expert with strong quantitative and statistical analysis capabilities.

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Skills

Core Skills

Quantitative ResearchMachine LearningStatistical Data Analysis

Other Skills

Microsoft ExcelPowerPointPythonTime-Series ModelingVBAИнвестицииКорпоративные финансыСтатистикаСтратегияТрейдингУправление активами и инвестициямиФинансовое моделированиеФинансовые рынкиФинансовый анализФинансы

About

Hold extensive experience in trading, quantitative and financial modelling and consulting

Experience

10 yrs 3 mos

Total Experience

3 yrs 5 mos

Average Tenure

3 yrs 9 mos

Current Experience

Algoquant (crypto quant fund)

Head of quant team

Sep 2022 – Present · 3 yrs 9 mos · Global · Remote

Team Leadership: Led a team of two quantitative researchers. Structured and planned the research process, broke down projects into workstreams, assigned responsibilities, conducted rigorous code reviews, and ensured timely execution.
Medium-Latency Statistical Arbitrage: Designed and deployed strategies operating in the 5s–1m range, achieving Sharpe 2 and 16% annual returns on capital of $5M.
LLM-Driven News Trading: Developed news-driven trading strategies using LLMs via advanced prompt engineering and custom API integration.
Directional Low-Frequency Strategies: backtest Sharpe 2.5 and 25% annual returns on macro/directional models.
ML / AI Pipelines: Built end-to-end machine learning pipelines including data ingestion, feature engineering, model selection (via AutoML / Optuna), and deployment.
Funding rate arbitrage: cross exchange perp – perp 12% unlevered returns, 4 Sharpe.
Investment Committee: Contributed to key decisions on strategy inclusion, portfolio allocation, slippage modeling, and market regime classification.
Developed company-wide solution for hyperparameter optimization based on Combinatorial Cross Validation that is resistant to overfitting.

Quantitative ResearchStatistical Data AnalysisMachine LearningPython

Boston consulting group (bcg)

Associate

Jun 2018 – Jul 2020 · 2 yrs 1 mo · Moscow, Russia

Retail:
Did category reset with tha aim to increase sales and margin
Developed initiatives in the areas of staff motivation, supply chain, pricing and planogramming
Expected results were 4% sales and 1% margin increase
Financial Institutions: customer journey transformation for multiple Russian banks, including:
Analysis of current customer journey state and painpoints and development of improvement initiatives
Creation of breakthrough saving product uniting deposits and investment products
Analysis of best world practices in the area of savings and investments
Management of client team
Oil&Gas: Participated in modification of investment reglament for Upstream business of major oil company

Ostc ltd.

Derivatives trader

Jan 2014 – Jun 2018 · 4 yrs 5 mos · Moscow

Traded energy, agricultural and STIR futures across global markets (CME, ICE) using calendar spreads and delta - neutral trading strategies.
Built market response models using VBA for momentum following strategies
Created time - series models for statistical arbitrage in EVIEWS. Developed ARIMA and ARIMAX models.
Initiated the project to apply Martingale principle to Light Sweet Oil price movement for further development of algo-trading.
0.4 million GBP AUM.
12% average annualized return over past 36 months.

Statistical Data AnalysisVBATime-Series Modeling