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Senior Data Scientist

2 months ago

New York, United States GradBay Full time

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.