Senior Quant Research Engineer, Trading & Portfolio Optimization

About Arta Finance

Arta is on a mission to make financial products once reserved for ultra-high-net-worth individuals accessible globally. We leverage AI and sophisticated digital tools to provide intelligent investment strategies, alternative assets, private market access, and smart automation. We value trust, teamwork, and adaptability.

The Role

We're seeking a Senior Quant Research Engineer to design the models that determine portfolio holdings and build the systems that execute trades efficiently at scale. This hybrid role combines rigorous portfolio theory with production engineering. You'll report to the CIO, working closely with investment and engineering teams to deliver real outcomes for thousands of client accounts.

We need someone with market experience and portfolio management judgment—not just abstract theoretical knowledge.

Key Responsibilities

• Design and improve models that determine target portfolio allocations, balancing risk, return, and client-specific constraints
• Build and maintain systems that translate allocations into real trades, emphasizing tax efficiency and cost-aware execution
• Apply portfolio optimization, factor-based risk modeling, and statistical estimation to keep strategies robust
• Backtest and validate new models against historical data before deploying to live portfolios
• Contribute investment and portfolio management perspectives to technical tradeoffs
• Partner with investment, product, and engineering teams to ship production-quality systems
• Use AI coding tools as part of daily research and development workflow

What You Bring

• 5+ years of experience as a quant researcher, trader, or in advisory/portfolio management roles
• Deep intuition for how portfolio systems should behave in real markets
• Strong foundation in portfolio theory, optimization, and risk management
• Proven ability to build and ship production systems at scale
• Experience with backtesting, tax-loss harvesting, or execution optimization
• Comfort working with rigorous quantitative methods and statistical modeling
• Ability to translate investment ideas into engineered systems