Quant Data Analyst in Machine Learning Team‬ (#1045)

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 strategies
• Experience in the management of a portfolio of algorithmic strategies
• Experience with data science for Agentic AI and Machine Learning
• Experience in the DeFi, DeFAI, or market-making
• Good knowledge of Finance for markets

What’s in it for you?

• Opportunity to deal with top-notch technologies and approaches in a world-leader product company with millions of customers
• Opportunity to make a difference for online privacy, freedom of speech, and net neutrality
• Decent market rate compensation depending on experience and skills
• Developed corporate culture: no micromanagement, culture based on principles of truth, trust, and transparency
• Support of personal and professional development
  • coverage of costs of external trainings, conferences, professional literature
  • support of experienced colleagues
  • in-house events and trainings
  • regular knowledge sharing in teams
  • English classes and speaking clubs
• Life-balance support
  
  • 25 working days of vacation
  • 5 days of paid sick leave per year without providing a medical certificate (no limitation on sick leaves with medical confirmation)
  • generous maternity / paternity leave program
• Professionally strong environment, friendly and open atmosphere, ability to influence the product development and recognition for it

You 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 strategy
• Participate in the full lifecycle of algorithmic strategy development: ideation, data research, strategy design and prototyping, backtesting, implementation, and live monitoring
• Systematically monitor and analyze strategy performance metrics, research and generate hypotheses for improvement, and iteratively test hypotheses
• Define requirements for implementation by Developers of algorithmic strategies and their data pipelines