Senior Data Scientist

2 weeks ago

New York, New York, United States GradBay Full time
Senior Data Scientist

GradBay is seeking a highly skilled Senior Data Scientist to join our team of world-class professionals. As a Senior Data Scientist, you will play a pivotal role in advancing our data-driven initiatives, working closely with traders, quantitative analysts, and other stakeholders to solve complex business challenges.

Key Responsibilities:

  • Develop advanced models and analytics to optimize financial strategies, risk assessments, and decision-making processes.
  • 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:

  • 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.

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