The Workforce Planning (WFP) organization at JPMorganChase is looking to deliver quantitatively driven solutions to support core WFP functions, including demand forecasting, capacity planning, resource scheduling, and business analysis & support, by leveraging data science and machine learning.
Requirements
- 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.).
- 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)
Responsibilities
- Design and development of Machine Learning, Artificial Intelligence and Statistical models.
- Participate in the full model development lifecycle, from framing the problem to prepare documentation and passing independent model review (MRGR).
- Lead AI/ML projects along with mentor and coach junior team members.
- 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 date 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.
Other
- Master’s Degree with 5+ years or Doctorate (PhD) with 3+ years of experience operating as an data science professional
- 2+ years of experience leading AI/ML projects with multiple team members
- Demonstrated relationship building skills, with a superior ability to make things happen through the use of positive influence.
- This position is full time in office Monday - Friday. This position is not hybrid nor remote.
- We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location.
