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J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. In accordance with applicable law, we make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as any mental health or physical disability needs.
The Corporate & Investment Bank is a global leader across investment banking, wholesale payments, markets and securities services. The world’s most important corporations, governments and institutions entrust us with their business in more than 100 countries. We provide strategic advice, raise capital, manage risk and extend liquidity in markets around the world.
The Global Payment Guardian is Wholesale Payment’s world class fraud screening application. We are is currently in need of a Machine Learning Engineer, VP to join our fast-growing team. The ideal candidate will be intricately involved in running analytical experiments in a methodical manner and will regularly evaluate alternate models via theoretical approaches. This is a great opportunity for the successful candidate to become a part of an innovative team that analyzes data to develop tools to help fight payment fraud for our clients.
Responsibilities
·         Collaborate with business, operations and other technology colleagues to understand company needs and devise possible solutions
·         Research and analyze data sets using a variety of statistical and machine learning techniques
·         Communicate results and ideas to key decision makers
·         Document approach and techniques used
·         Work on longer term projects, building tooling that can be used to scale certain types of analyses across multiple datasets and business use cases
·         Collaborate with other J.P. Morgan machine learning teams
·         Keep up-to-date with latest technology trends
Required Technical Qualifications and experience
·         MS or PhD in a Data Science or related discipline, e.g. Computer Science, Applied Mathematics, Statistics, Physics, Artificial Intelligence
·         Advanced data mining and EDA (Exploratory Data Analysis) skills
·         Strong ability to develop and debug in Python (must) and Java (would be a plus)
·         3+ years experience with machine learning APIs and computational packages (examples: TensorFlow, LightGBM, PyTorch, Keras, Scikit-Learn, NumPy, SciPy, Pandas, H2O, SHAP, Catboost)
·         Good experience with model explainability
·         5 + years of experience with big-data technologies such as Hadoop, Spark, SparkML, etc
·         Able to understand various data structures and common methods in data transformation
·         Excellent pattern recognition and predictive modeling skills
·         Experience with large imbalanced datasets
Other experience and qualifications
·         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 independently research and propose alternatives with some guidance as to problem relevance
·         Experience with fraud detection
·         Should be able to work both individually and collaboratively in teams, in order to achieve project goals
·         Able to work with non-specialists in a partnership model, conveys information clearly and creates a sense of trust with stakeholder
·         Ensures re-use and sharing of ideas within team and locale
RequisitionType Professional JobSchedule Full time