About the Role
The role involves designing and implementing NLP-driven models and quantitative strategies to analyze market signals and improve trading outcomes.
Responsibilities
- Develop and refine natural language processing models for financial text analysis
- Extract insights from news, social media, and earnings reports using NLP techniques
- Build predictive models to identify market-moving events and sentiment shifts
- Collaborate with trading teams to integrate NLP outputs into execution strategies
- Design and test quantitative trading algorithms based on textual and market data
- Evaluate model performance using historical and real-time financial data
- Optimize feature engineering pipelines for unstructured text inputs
- Work with large datasets from diverse financial and news sources
- Ensure models are robust, scalable, and production-ready
- Monitor live trading performance and adjust models as needed
- Conduct backtesting and simulation of trading strategies
- Improve data quality and preprocessing workflows
- Stay current with advancements in NLP and quantitative finance
- Document research methodologies and model decisions
- Support deployment of models into production trading systems
- Collaborate with data engineers to streamline data pipelines
- Apply statistical methods to validate model accuracy and significance
- Identify new data sources that can enhance predictive power
- Communicate findings and recommendations to quantitative researchers
- Maintain high standards for code quality and reproducibility
Nice to Have
- PhD in a relevant technical field
- Published research in NLP or computational finance
- Experience with transformer models and large language models
- Background in high-frequency or algorithmic trading
- Knowledge of market microstructure
- Experience with alternative data sources
- Familiarity with reinforcement learning for trading
- Contributions to open-source data science projects
- Experience in a fast-paced trading environment
Compensation
Competitive salary and performance-based incentives
Work Arrangement
Flexible work environment with remote and on-site options
Team
Collaborative team focused on quantitative research and algorithmic trading
What We Look For
- Candidates should demonstrate a strong analytical mindset and the ability to innovate in complex data environments.
- We value practical experience in deploying models that drive measurable trading performance.
- A passion for financial markets and data-driven decision-making is essential.
Application Process
- Applicants must submit a resume and a brief summary of relevant projects.
- Shortlisted candidates will complete a technical assessment and interview rounds.
- Final stages include discussions with research and trading team leads.
Available for qualified candidates
