JPMorgan Lead Security Engineer - Data Scientist 

United States, Virginia 

452676599

Job responsibilities

• Works with stakeholders and business leaders to understand security needs and recommend business modifications during periods of vulnerability.
• Work with cybersecurity engineers and data engineers to acquire data that addresses each use case (fraud, anomaly detection, Cyber threats).
• Perform Exploratory Data Analysis on datasets and communicate results to stakeholders.
• Select statistical or Deep Learning models that are best positioned to achieve business results.
• Perform feature engineering or hyperparameter tuning to optimize model performance.
• Perform model governance activities for model interpretability, testability and results.
• Executes creative security solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions and break down technical problems.
• Develops secure and high-quality production code and reviews and debugs code written by others.
• Minimizes security vulnerabilities by following industry insights and governmental regulations to continuously evolve security protocols, including creating processes to determine the effectiveness of current controls.
• Adds to team culture of diversity, equity, inclusion, and respect.

Required qualifications, capabilities, and skills

• Formal training or certification on security engineering concepts and 5+ years applied experience.
• Advanced in one or more programming languages
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• In-depth knowledge of the financial services industry and their IT systems
• 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 Keras, Tensorflow or PyTorch
• Experience with feature engineering complex datasets.
• Possess the ability to explain model selection, model interpretability and performance metrics verbally and in writing.

Preferred qualifications, capabilities, and skills

• Experience deploying Statistical or Machine Learning models via AWS SageMaker in a production setting
• Working knowledge of Large Language Models (LLM), NLP, Embeddings and Retrieval Augmented Generation (RAG)
• Experience with model monitoring and understanding data quality issues
• Experience with Retrieval Augmented Generation (RAG) applications and the frameworks used to create them such as Langchain or Llamaindex
• Working knowledge of Responsible AI, model fairness, and reliability and safety
• Bachelor's egree in Data Science, Mathematics, Statistics, Econometrics or Computer Science and 3+ years data-science experience (Exploratory Data Analysis, statistical analysis and reporting results).