Location : Remote
Your expertise :
- High personal interest in quantitative and algorithmic approaches
- Knowledge in quantitative analysis, statistics, time-series analysis, ML modeling and forecasting for markets
- Experience from 2 years with Data Science activities, including data research and analysis, algorithmic strategy prototyping and backtesting
- Experience with creating and supporting algorithmic strategies, including their risk management
- Experience in systematically monitoring and evaluating the performance of algorithmic strategies with a set of KPIs
- Experience with SQL, Pandas / NumPy / SciPy, and backtesting frameworks
Will definitely be a plus :
Experience with effectively managing delta-neutral and grid strategiesExperience in the management of a portfolio of algorithmic strategiesExperience with data science for Agentic AI and Machine LearningExperience in the DeFi, DeFAI, or market-makingGood knowledge of Finance for marketsWhat’s in it for you?
Opportunity to deal with top-notch technologies and approaches in a world-leader product company with millions of customersOpportunity to make a difference for online privacy, freedom of speech, and net neutralityDecent market rate compensation depending on experience and skillsDeveloped corporate culture : no micromanagement, culture based on principles of truth, trust, and transparencySupport of personal and professional development
coverage of costs of external trainings, conferences, professional literaturesupport of experienced colleaguesin-house events and trainingsregular knowledge sharing in teamsEnglish classes and speaking clubsLife-balance support
25 working days of vacation5 days of paid sick leave per year without providing a medical certificate (no limitation on sick leaves with medical confirmation)generous maternity / paternity leave programProfessionally strong environment, friendly and open atmosphere, ability to influence the product development and recognition for itYou will be involved into :
Lead Data Science activities for algorithmic strategies : data research and analysis, prototyping and backtesting, live strategy performance monitoring, designing data pipelines, designing and implementing risk management strategyParticipate in the full lifecycle of algorithmic strategy development : ideation, data research, strategy design and prototyping, backtesting, implementation, and live monitoringSystematically monitor and analyze strategy performance metrics, research and generate hypotheses for improvement, and iteratively test hypothesesDefine requirements for implementation by Developers of algorithmic strategies and their data pipelines