AI ML Associate
There’s nothing more exciting than being at the center of a rapidly growing field in technology and applying your skillsets to drive innovation and modernize the world`s most complex and mission-critical systems
In Risk Management & Compliance Technology, Machine Learning at JPMorgan Chase, our role involves solving challenging business problems such as Anti-Money Laundering and Surveillance through data science and machine learning techniques across Risk, Compliance, Conduct and Operational Risk. The Data Scientist is an individual contributor that should be able to apply quantitative, data science and analytical skills to complex problems. He/she should be able to work across teams to design, develop, and evaluate and execute against those data science and analytical solutions with a keen functional understanding of the business problem. He/she will be responsible for data wrangling, data analysis, modeling, including model selection and producing quick applicable modeling solutions
Job responsibilities
- The position will serve as a senior associate advising on optimal solutions and opining on challenger models
- The role works on strategic, highly visible projects firm wide providing an opportunity to have meaningful impact on a large scale at a leading financial services firm
- The role will develop data-centric solutions that move the bottom line for the firm
- In Risk Management & Compliance Technology Machine Learning at JPMorgan Chase, our role involves solving challenging business problems such as Anti-Money Laundering and Surveillance through data science and machine learning techniques across Risk, Compliance, Conduct and Operational Risk
Required qualifications, capabilities, and skills
- Formal training or certification on AI ML engineering concepts and 3+ years applied experience
- Advanced degree in analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis, Operations Research)
- Extensive practical expertise and work experience with Machine Learning, both supervised and unsupervised. Deep Learning (neural network) experience is preferred
- Min 5 years Experience across broad range of modern analytic and data tools, particularly Python/Anaconda and/or R, XG-Boost, Tensorflow and/or Keras, Spark, Hive, SQL
- Experience working with engineering teams to operationalize Machine Learning models
- Excellent problem solving, communications, and teamwork skills
Preferred qualifications, capabilities, and skills
- Financial service background preferred, but not required
- Advanced ML Techniques
- Ability to work NLP / Deep Learning Algorithms, self-Starter
- Presentation/Communication Skills
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