|Job Type:||Full Time|
About Data Analytics within Corporate & Investment Bank
Data Analytics at J.P. Morgan Corporate Investment Bank 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 industry-leading data analytics team, and advance the state-of-the-art in financial applications ranging from generating business intelligence to predictive models and automated decision making.
The role will be in the firm’s Applied AI and Machine Learning organization and will involve working closely with Digital & Platform Services Operations.
The Digital & Platform Services Operations teams support the Corporate & Investment Bank and functions including Technology, Data Science, Client Service, Product and Platform as well as other businesses and stakeholders across the firm.
The successful candidate will apply data analytics techniques from both traditional statistics and machine learning to a combination of third party, publically available and J.P. Morgan proprietary datasets, with the goal of answering questions relevant to Digital & Platform Services Operations.
-Collaborate with Operations colleagues to formulate relevant financial and business questions that can be answered by data analysis.
-Research and analyze data sets using a variety of statistical and machine learning techniques
-Communicate final results and give context.
-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.
Required TechnicalQualifications, experience & behaviours
-MS or PhD in a quantitative discipline, e.g.Computer Science, Mathematics, Statistics, Operations Research, Data Science,or similar BS with experience in a highly quantitative position.
-Hands-on experience analyzing data.
-Strong ability to develop and debug in Python orsimilar professional programming language.
-Problem solving and collaboration skills
-Should be able to work both individually andcollaboratively in teams, in order to achieve project goals.
-Must be curious, hardworking anddetail-oriented, and motivated by complex analytical problems.
-Must have the ability to design or evaluateintrinsic and extrinsic metrics of your model’s performance which are alignedwith business goals.
-Must be able to independently research andpropose alternatives with some guidance as to problem relevance.
-Must be able to undertake basic and advancedEDA, may require some direction from more senior team; should be aware oflimitation and implication of methodology choices.
-Ensures re-use and sharing of ideas within teamand locale.
Nice to Have
-Ideally, some experience with machine learningAPIs and computational packages (examples: TensorFlow, Theano, PyTorch, Keras,Scikit-Learn, NumPy, SciPy, Pandas, statsmodels).
-Experience with big-data technologies such asHadoop, Spark, SparkML, etc.
-Able to work with non-specialists in apartnership model, conveys information clearly and creates a sense of trustwith stakeholders.
-Shows institutional awareness and someunderstanding of applied problem solving, may require coaching and guidance asto how to most rapidly reach a satisfactory conclusion
The hiring manager for this job opening wouldwelcome a conversation about flexible working. This could range from adhoc flexibility in a full time position, to a more formal Flexible WorkArrangement.