Data Scientist Associate - Workforce Planning

Join the AI/ML team in building next-gen data science solutions for real-time inference and decision-making.

As a Data Scientist Associate in Workforce Planning, you will tackle complex, data-intensive projects with significant business impact. You'll assess unstructured problems, devise practical strategies, analyze topics, and develop solution proposals. Collaborate with management to prioritize, time, and deliver results.

The Workforce Planning (WFP) organization is a part of Consumer and Community (CCB) Operations division. The WFP Data Science organization is tasked with delivering quantitatively driven solutions to support the core WFP functions (demand forecasting, capacity planning, resource scheduling, and business analysis & support). The WFP organization supports Chase's call centers, back office, and ~5,200 retail branches.

Job Responsibilities

• Design and development of Machine Learning, Artificial Intelligence and Statistical models.
• Support AI/ML simpler projects individually or more complex as part of a project team.
• Collaborate with stakeholders to understand the business requirements and clearly define the objectives of any solution.
• Identify and select the correct method to solve the problem while staying up to data on the latest AI/ML research.
• Ensure the robustness of any data science solution.
• Develop and communicate recommendations and data science solutions in easy-to-understand-way leveraging data to tell a story.
• Able to work effectively and gain credibility and respect of others including peers, clients and other stakeholders.

• Master's Degree with 1+ years or Doctorate (PhD) with 0+ years of experience operating as an data science professional (e.g. data scientist, statistician, or related professions) in a quantitative field: Statistics, Analytics, Data Science, Engineering, Operations Research, Economics, Mathematics, Machine Learning, Artificial Intelligence, and related disciplines.
• Experience supporting AI/ML projects with multiple team members.
• Hands-on experience developing statistical models, machine learning models, and/or artificial intelligence models.
• Deep understanding of math and theory behind AI/ML algorithms.
• Proficient in data science programming languages like Python, R or Scala.
• Experience with big-data technologies such as Hadoop, Spark, SparkML, etc. & familiarity with basic data table operations (SQL, Hive, etc.).
• Demonstrated relationship building skills, with a superior ability to make things happen through the use of positive influence.

• Advanced expertise with Time Series and Operations Research techniques.
• Natural Language Processing(NLP)/Natural Language Generation(NLG), Neural Nets, or other ML/AI skills.
• Prior experience with public cloud technologies such as Amazon Web Services(AWS), Azure or Google Cloud Platform(GCP).
• Previous experience leading highly complex cross-functional technical projects with multiple stakeholders.