Data Scientist - Sr. Associate

Key Skills

Java Programming, Python Programming, SQL, Apache Hadoop, Keras software library, TensorFlow, XGBoost, Apache Hive, R Programming, SPARK Programming

Job Description

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.

The position will serve as a thought leader including advising on optimal solutions and opining on challenger models. The role works on strategic, highly visible projects firm wide. It is 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.

HR Data and Analytics is a centralized global team responsible for all aspects of workforce data strategy, analytics and reporting, and governance, and includes the development of artificial intelligence and machine learning (AI/ML) based solutions. We have a vision to help make individuals, teams, and businesses at JPMC among the most engaged and productive in the world.

This role requires a wide variety of strengths and capabilities, including:

• Advanced degree in analytical fimodels. The role works on strategic, highly visible projects firm wide. It is 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.

  HR Data and Analytics is a centeld (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
• Experience across broad range of modern analytic and data tools, particularly Python/Anaconda and/or R, XGBoost, Tensorflow and/or Keras, Spark, Hive, SQL
• Experience working with engineering teams to operationalize Machine Learning models
• Excellent problem solving, communications, and teamwork skills
• Financial service background preferred, but not required