Machine Learning Scientist - Natural Language Processing; NLP - Sr. Associate - Machine Learni

Machine Learning Scientist - Natural Language Processing (NLP) - Sr. Associate - Machine Learning Center of Excellence

Seattle, WA, United States

Location(s): 1201 3

Rd Ave, Seattle, WA, 98101, US; 3223 Hanover St, Palo Alto, CA, 94304, US; 383 Madison Ave, New York, NY, 10179, US

• Job Identification:
• Job Category:
  Predictive Science
• Business Unit:
  Corporate Sector
• Posting Date: 30/10/2024, 15:56
• Locations: 1201 3
  
  Rd Ave, Seattle, WA, 98101, US; 3223 Hanover St, Palo Alto, CA, 94304, US; 383 Madison Ave, New York, NY, 10179, US
• Job Schedule:
  
  Full time
• Base Pay/Salary:
  Palo Alto,CA $-$;
  New York,NY $-$;
  Seattle,WA $-$

The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm’s data and analytics journey. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.

As a Machine Learning Scientist - Natural Language Processing (NLP) - Senior Associate in the Machine Learning Center of Excellence, you will apply sophisticated machine learning methods to complex tasks including natural language processing, speech analytics, time series, reinforcement learning and recommendation systems. You will collaborate with various teams and actively participate in the knowledge sharing community. You should excel in working in a highly collaborative environment together with the business, technologists and control partners to deploy solutions into production.

You should also have a strong passion for machine learning and invest independent time towards learning, researching and experimenting with new innovations in the field. You should have solid expertise in Deep Learning with hands-on implementation experience and possess strong analytical thinking, a deep desire to learn and be highly motivated.

The candidate must excel in working in a highly collaborative environment together with the business, technologists and control partners to deploy solutions into production. The candidate must also have a strong passion for machine learning and invest independent time towards learning, researching and experimenting with new innovations in the field. The candidate must have solid expertise in Deep Learning with hands-on implementation experience and possess strong analytical thinking, a deep desire to learn and be highly motivated.

The candidate must excel in working in a highly collaborative environment together with the business, technologists and control partners to deploy solutions into production. The candidate must also have a strong passion for machine learning and invest independent time towards learning, researching and experimenting with new innovations in the field. The candidate must have solid expertise in Deep Learning with hands-on implementation experience and possess strong analytical thinking, a deep desire to learn and be highly motivated.

• Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community
• Develop state‑of‑the‑art machine learning models to solve real‑world problems and apply it to tasks such as NLP, speech recognition and analytics, time‑series predictions or recommendation systems
• Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production
• Drive firm‑wide initiatives by developing large‑scale frameworks to accelerate the application of machine learning models across different areas of the business

• PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science…