Chase · 3 hours ago
CCB Risk Program Associate
8181 Communications Pkwy Bldg A, Plano, TX, 75024, US
Full-time
Onsite
Entry, Mid Level
2+ years expChase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. As a Risk program Senior Associate within the Chase Consumer Bank, you'll be the analytical expert for identifying and retooling suitable machine learning algorithms that can enhance the fraud risk ranking of transactions and applications for new products.
BankingFinancial Services
Responsibilities
Identify and retool machine learning (ML) algorithms to analyze datasets for fraud detection in the Chase Consumer Bank
Perform machine learning tasks such as feature engineering, feature selection, and developing and training machine learning algorithms using cutting-edge technology to extract predictive models/patterns from billions of transactions’ amounts of data
Collaborate with business teams to identify opportunities, collect business needs, and provide guidance on leveraging the machine learning solutions
Interact with a broader audience in the firm to share knowledge, disseminate findings, and provide domain expertise
Qualification
Required
Master's degree in Mathematics, Statistics, Economics, Computer Science, Operations Research, Physics, and other related quantitative fields
2 years of experience with data analysis in Python
Some Experience in designing models for a commercial purpose using some (at least 3) of the following machine learning and optimization techniques: CNN, RNN, SVM, Reinforcement Learning, Random Forest/GBM
A strong interest in how models work, the reasons why particular models work or not work on particular problems, and the practical aspects of how new models are designed
Preferred
PhD in a quantitative field with publications in top journals, preferably in machine learning
Experience with model design in a big data environment making use of distributed/parallel processing via Hadoop, particularly Spark and Hive
Experience designing models with Keras/TensorFlow on GPU-accelerated hardware
Experience with graph technology, including designing and implementing graph-based machine learning models for fraud detection or risk assessment. Familiarity with graph databases (such as TigerGraph or Neo4j …), graph algorithms (e.g., node classification, link prediction, community detection), and graph feature engineering is highly desirable. Ability to leverage graph analytics to uncover complex relationships and patterns within large-scale transaction data is a strong plus
Hands-on experience with transformer models and related architectures (such as BERT, GPT, or Graph Transformers) for natural language processing, anomaly detection, or transaction analysis. Proficiency in fine-tuning and deploying transformer-based models using frameworks like PyTorch or TensorFlow is preferred. Demonstrated ability to apply transformer models to extract meaningful insights from unstructured or semi-structured data sources will be highly valued
Benefits
Comprehensive health care coverage
On-site health and wellness centers
A retirement savings plan
Backup childcare
Tuition reimbursement
Mental health support
Financial coaching
Company
Chase
Chase provides broad range of financial services. It is a sub-organization of JP Morgan Chase.
10001+ employees
Funding
Current Stage
Late StageLeadership Team
Mike McDonnell
Managing Director, Head of Chase Travel Platform Product
Nicole Sanchez
Managing Director, Consumer Bank, GM and Product Executive, Growth Financial Products
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