The Business
Join one of the world’s leading investment banks at the forefront of financial innovation. We leverage cutting-edge data science and machine learning techniques to drive high-impact decisions across global markets, risk management, and client strategies. As a Senior Data Scientist, you will play a pivotal role in advancing our data-driven initiatives, working with a diverse team of world-class professionals.
The Job
As a Senior Data Scientist, you will be responsible for developing advanced models and analytics to optimize financial strategies, risk assessments, and decision-making processes. You’ll collaborate closely with traders, quantitative analysts, and other stakeholders to solve complex business challenges, driving profitability and operational efficiency through data-driven insights.
Key Responsibilities:
- Lead the design, development, and implementation of cutting-edge machine learning models and algorithms to solve business problems in trading, risk management, and investment strategies.
- Collaborate with cross-functional teams to identify opportunities for leveraging data to drive business solutions.
- Analyze large, complex datasets to extract actionable insights that will influence strategic decision-making.
- Develop and maintain robust predictive models for various financial instruments, leveraging advanced techniques such as deep learning, NLP, and time-series forecasting.
- Work closely with data engineering teams to ensure efficient data collection, processing, and pipeline development.
- Present analytical findings to senior stakeholders, translating complex results into clear, actionable recommendations.
- Stay updated on the latest developments in data science, machine learning, and AI to ensure the application of cutting-edge methodologies.
- Mentor junior data scientists and contribute to fostering a culture of innovation and excellence within the team.
Candidate Requirements
Required Qualifications:
- Educational Background:
- PhD in a quantitative field is essential (e.g., Data Science, Machine Learning, Statistics, Mathematics, Computer Science, Engineering, or related disciplines).
- Experience:
- 5+ years of experience in data science or machine learning, with a strong track record of delivering results in a fast-paced, high-stakes environment.
- Previous experience in financial services, investment banking, or a related industry is highly desirable.
- Technical Skills:
- Expert proficiency in programming languages such as Python or R.
- Strong experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Proficiency in SQL and experience working with large-scale, unstructured datasets.
- Experience with data visualization tools (e.g., Tableau, Power BI) and communicating complex data insights.
- Familiarity with cloud platforms (AWS, GCP, Azure) and big data technologies (e.g., Hadoop, Spark).
- Quantitative Skills:
- Strong background in statistics, probability theory, and mathematical modeling.
- Experience with advanced machine learning techniques such as deep learning, reinforcement learning, and natural language processing.
Desirable Skills:
- Experience in developing and deploying real-time models in production environments.
- Knowledge of financial markets, trading strategies, or risk management frameworks.
- Familiarity with DevOps practices and software engineering best practices.
