• JP Morgan Chase
  • $145,793.33 -49,680.00/year*
  • New York , NY
  • Information Technology
  • Full-Time
  • 411 Grand St


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The Machine Learning Center of Excellence combines cutting edge machine learning techniques with the company s unique data assets to optimize all the business decisions we make. In this role, you will be part of our world-class machine learning team, and advance the state-of-the-art in financial applications ranging from pricing and credit models to natural language processing. Our work spans the company s lines of business, with exceptional opportunities in each. The successful candidate will develop new machine learning methods tailored to banking applications such as risk assessment, trading models, customer relationship management, and pricing models. Machine learning techniques will include feed-forward, recurrent, recursive and convolutional neural networks, maximum entropy models, and other algorithms related to time series analysis and supervised learning. In addition to using and adapting existing models, you will be expected to develop new techniques especially suited to banking applications. The candidate will help in the identification and solution of new problem areas. Responsibilities Develop scalable tools leveraging machine learning and deep learning models to solve real-world problems in areas such as Speech Recognition, Natural Language Processing and Time Series predictions. Collaborate with all of JPMorgan Chase's lines of businesses, such as Investment Bank, Commercial Bank, and Asset Management. Lead your own project. Suggest, collect and synthesize requirements. Create an effective roadmap towards the deployment of a production-level machine learning application. MS or PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Operations Research, Data Science, or similar BS with 2+ years of experience in a highly quantitative position. Experience in Deep Learning: DNN, CNN, RNN/LSTM, GAN or other auto encoder (AE). 2+ years of hands-on experience developing machine learning models. Ability to develop and debug in Python, Java, C or C++. Proficient in git version control. R and Matlab are also relevant. Extensive experience with machine learning APIs and computational packages (TensorFlow, Theano, PyTorch, Keras, Scikit-Learn, NumPy, SciPy, Pandas, statsmodels). Familiarity with basic data table operations (SQL, Hive, etc.) Should be able to work both individually and collaboratively in teams, in order to achieve project goals. Must be curious, hardworking and detail-oriented, and motivated by complex analytical problems. Must have the ability to design or evaluate intrinsic and extrinsic metrics of your model s performance which are aligned with business goals. Must be able to effectively communicate technical concepts and results to both technical and business audiences. Beneficial Skills Solid time series analysis, speech recognition, NLP or financial engineering background. Strong background in Mathematics and Statistics. Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal. Not ready to apply? Leave your information with us and we will keep you up to date with new career opportunities. Any information you provide is confidential and will only be viewed by our recruiters in an effort to fill open positions. In addition, the information you provide is subject to our privacy policy practices. Please note that J.P. Morgan will not accept unsolicited approaches or speculative CVs, nor will J.P. Morgan be responsible for any related fees, from Third Party Firms who are not preferred suppliers. The firm invites all interested and qualified candidates to apply for employment opportunities. Need disability related assistance? If you are a US or Canadian applicant with a disability who is unable to use our online tools to search and apply for jobs, please click here.
Associated topics: c++, c#, computer network, etl, information technology infrastructure library, j2ee, java, machine learning, oracle, website

* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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