JPMorgan Lead Applied Machine Learning Scientist 

United States, California, Palo Alto 

561645531

As an Applied Machine Learning Scientist in Trust & Safety for the Payments Organization, you will be involved in developing machine learning models that facilitate safe & secure SMB payments by detecting and mitigating Fraud Risk. You will experiment with various relevant Al & ML algorithms and techniques to build best-in-class solutions as part of the organization that oversees several trillion dollars of Wire/ACH transactions and hundreds of millions of card transactions.

Job Responsibilities

• Build machine learning systems and models for detecting payment fraud, merchant fraud, and merchant risk
• Research and analyze large data sets using advanced exploratory techniques and communicate findings to key stakeholders
• Drive and own the complete lifecycle from data extraction, model development through model deployment and production evaluation/maintenance
• Design and Implement Knowledge graph capturing information from various 3rd party/partner data sources and relationships therein
• Collaborate closely with Business, operations and Product teams to devise effective Risk and Fraud solutions.
• Bring an AI/ML first thinking to our Fraud/Risk solutions and thus achieving operational excellence.
• Design and Implement Knowledge graph capturing information from various 3rd party/partner data sources and relationships therein
• Collaborate closely with Business, operations and Product teams to devise effective Risk and Fraud solutions.

Required Qualifications, Capabilities and Skills:

• MS or Ph.D. in Machine Learning, Data Science or related discipline, e.g. Computer Science, Applied Mathematics, Statistics, Physics, Artificial Intelligence
• In-depth understanding of machine learning and modeling algorithms such as decision trees, random forest, neural networks, graph models
• Technical expertise in data preprocessing, feature extraction, model building, and statistical analysis
• Proficiency in databases (SQL), and programming languages (at least one of the following: Python or Java)
• 3+ years experience with machine learning APIs and computational packages like XgBoost, Pandas, TensorFlow, Scikit-Learn, NumPy, SciPy
• 5 + years of experience with big-data technologies such as Hadoop, Spark, Flink.

Preferred qualifications, capabilities, and skills

• Past AI/ML experience in Payments is a big plus.