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Our team of engineers, quantitative researchers and data scientists looks beyond the traditional to test hypotheses and develop creative solutions to some of the world’s most complex economic problems. We are seeking a self-motivated individual to join the Execution Modeling team. The team researches and builds the tactics, models, and all market interactions that drive how we trade across Global Equities and Global Macro. We are seeking a quantitative researcher to reduce execution costs and increase capacity through market microstructure research impacting trading algorithms, market impact models, interaction with portfolio construction, simulation, and scheduling. You will partner closely with experts across modeling, portfolio management, and trading to take research into production. This is a hands-on research role with the opportunity to shape the direction of execution research across regions and asset classes. You will take on the following responsibilities:
- Optimize how orders are scheduled and how that schedule interacts with the tactics underneath it and with portfolio optimizers
- Improve our execution simulator and its agreement with production results, including fill probability, adverse selection, and post-trade impact
- Research and develop short-horizon signals from order book, quote, and trade data to improve trading tactics, order placement, and venue selection
- Build and improve market impact models across trading horizons, from seconds to multiple days, and across instruments with very different liquidity profiles
- Design and analyze production experiments (A/B tests) and execution performance metrics that separate real improvements from market noise
- Use our large internal history of orders and fills to find new sources of execution alpha
- Build relationships with other teams supporting investment and research processes, and work closely with multiple teams on joint research
You should possess multiple of the following qualifications:
- Excellent quantitative skills, as evidenced by formal training in statistics, applied mathematics, operations research, economics, computer science, physics, engineering, or a related quantitative field. A PhD is a plus but not required.
- 5-15 years of experience in execution research, algorithmic trading, market-making, or high-frequency trading at a financial firm.
- Deep understanding of market microstructure, including order types, venues, dark pools, queue dynamics, and how different market participants behave
- Hands-on experience with market impact modeling, transaction cost analysis, or execution simulation
- Expertise with large datasets of intraday market data (quotes, trades, order book). Experience with full order-by-order (L3) data is a significant plus.
- Experience applying machine learning techniques to trading, execution, or modeling problems
- Strong programming skills (Python, Java, or C++), data management and retrieval skills, and literacy with Linux and LLM support
- Effective communication skills, both written and verbal
- Ability to own research end-to-end, from data gathering through hypothesis testing to production deployment and monitoring, in a fast-paced, team-oriented environment
- Core Benefits: Fully paid medical and dental insurance premiums for employees and dependents, competitive 401k match, employer-paid life & disability insurance
- Perks: Onsite gyms with laundry service, wellness activities, casual dress, snacks, game rooms
- Learning: Tuition reimbursement, conference and training sponsorship
- Time Off: Generous vacation and unlimited sick days, competitive paid caregiver leaves
- Hybrid Work Policy: Flexible in-office days with budget for home office setup
Two Sigma is committed to providing reasonable accommodations to qualified individuals in accordance with applicable federal, state, and local laws.
If you believe you need an accommodation, please visit our website for additional information.
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