About the position
Data Scientist:
Join a high-impact team focused on enhancing data quality and analytical capabilities within Global Markets. Collaborate with Sales, Trading, and IT to optimize market-making algorithms and leverage advanced machine learning on high-frequency trading data.
Key Responsibilities:
- Develop and optimize market-making models (equities and derivatives).
- Conduct model back testing and research for continuous improvement.
- Analyse high-frequency data to identify market patterns and trends.
- Apply ML techniques (e.g. LSTMs, CNNs) to predict short-term price movements.
- Work with AWS (S3, SageMaker) or similar cloud infrastructure.
- Perform time-based and volume-based data sampling.
- Collaborate to integrate models into production environments.
- Expand trading universes, enhance trader algos, and build new predictive indicators.
Must-Have Skills & Experience:
- 5-7 years in data analytics, machine learning, or quantitative analysis.
- Proficiency in Python, SQL, AWS (S3, SageMaker), and QuickSight.
- Strong understanding of equities, capital markets, and trading platforms.
- Hands-on with ML techniques, particularly time series and neural networks.
- Familiarity with market microstructure and high-frequency trading data.
- Experience with hedge funds (2+ years).
- Tools: Azure DevOps, ServiceNow.
Desirable Skills:
- Knowledge of technical indicators and trading systems.
- Experience in pre-/post-trade systems and high-frequency data techniques.
- Background in derivatives, risk systems, or treasury operations.
Job Type:
Workplace Type:
Location:
Experience Level:
If you believe that you have what it takes, please contact Kivara Rajgopal on [Email Address Removed] or [Phone Number Removed];
Desired Skills:
- Python
- SQL
- AWS
- Trading Data
- Azure Devops
- ServiceNow
- ML Techniques
Desired Qualification Level:
