Lead Data Scientist
On-site · McLean, Virginia, United States
Job Summary
Lead Data Scientist at JPMorgan Chase within the Cybersecurity and Technology Controls line of business, contributing as a core technical developer to deliver Machine Learning solutions that address fraud, anomaly detection, and cybersecurity use cases. Responsibilities include collaborating with stakeholders to understand security needs, acquiring data with cybersecurity engineers and data engineers, performing Exploratory Data Analysis, selecting and tuning statistical or deep learning models, performing feature engineering, ensuring model governance and interpretability, developing secure production-ready code, and adhering to security protocols and regulatory guidance. Proficiency in Python data-science stacks (Pandas, SQL, visualization tools), experience with Scikit-Learn and PyTorch, and familiarity with Generative AI/LLMs, transformers, and AWS SageMaker are highlighted as preferred capabilities.
Required Qualifications
- Formal training or certification on security engineering concepts and 5+ years applied experience
- Advanced in one or more programming languages
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Working knowledge of probability, statistics and statistical distributions and their applicability to use cases and the ability to perform Exploratory Data Analysis using Jupyter or SageMaker Notebooks
- Proficient in Pandas, SQL and Data Visualization tools such as Matplotlib, Seaborn or Plotly
- Working knowledge of Scikit-Learn for development of classification, regression and clustering models and Deep Learning frameworks such as PyTorch
- Experience with feature engineering complex datasets
- Possess the ability to explain model selection, model interpretability and performance metrics verbally and in writing
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