JPMorganChase
Machine Learning Scientist - Natural Language Processing (NLP) - Vice President
JPMorganChase, New York, New York, us, 10261
JOB DESCRIPTIONThe 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 Vice President in the Machine Learning Scientist - Natural Language Processing (NLP) team, you will be responsible for applying advanced machine learning techniques to a variety of complex tasks. These tasks include natural language processing, speech analytics, time series, reinforcement learning, and recommendation systems. You will work closely with different teams and actively contribute to our knowledge sharing community.
In a highly collaborative environment, you will partner with business professionals, technologists, and control partners to implement solutions into production. Your passion for machine learning should be evident, and you should be willing to dedicate time to learning, researching, and experimenting with new innovations in the field. Your expertise in Deep Learning, coupled with hands-on implementation experience, strong analytical thinking, a deep desire to learn, and high motivation, will be crucial for this role.
Job Responsibilities
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.
Required Qualifications, Capabilities, and Skills
PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science with three years of industry experience or an MS with at least five years of industry or research experience in the field.
Solid background in NLP or speech recognition and analytics, personalization/recommendation and hands-on experience and solid understanding of machine learning and deep learning methods.
Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas).
Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals.
Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments.
Curious, hardworking and detail-oriented, and motivated by complex analytical problems.
Preferred Qualifications, Capabilities, and Skills
Strong background in Mathematics and Statistics and familiarity with the financial services industries and continuous integration models and unit test development.
Knowledge in search/ranking, Reinforcement Learning or Meta Learning.
Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large scale distributed environment and ability to develop and debug production-quality code.
Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal.
ABOUT US
JPMorgan Chase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set, and location. For those in eligible roles, we offer discretionary incentive compensation which may be awarded in recognition of firm performance and individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company.
#J-18808-Ljbffr
As a Vice President in the Machine Learning Scientist - Natural Language Processing (NLP) team, you will be responsible for applying advanced machine learning techniques to a variety of complex tasks. These tasks include natural language processing, speech analytics, time series, reinforcement learning, and recommendation systems. You will work closely with different teams and actively contribute to our knowledge sharing community.
In a highly collaborative environment, you will partner with business professionals, technologists, and control partners to implement solutions into production. Your passion for machine learning should be evident, and you should be willing to dedicate time to learning, researching, and experimenting with new innovations in the field. Your expertise in Deep Learning, coupled with hands-on implementation experience, strong analytical thinking, a deep desire to learn, and high motivation, will be crucial for this role.
Job Responsibilities
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.
Required Qualifications, Capabilities, and Skills
PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science with three years of industry experience or an MS with at least five years of industry or research experience in the field.
Solid background in NLP or speech recognition and analytics, personalization/recommendation and hands-on experience and solid understanding of machine learning and deep learning methods.
Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas).
Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals.
Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments.
Curious, hardworking and detail-oriented, and motivated by complex analytical problems.
Preferred Qualifications, Capabilities, and Skills
Strong background in Mathematics and Statistics and familiarity with the financial services industries and continuous integration models and unit test development.
Knowledge in search/ranking, Reinforcement Learning or Meta Learning.
Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large scale distributed environment and ability to develop and debug production-quality code.
Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal.
ABOUT US
JPMorgan Chase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set, and location. For those in eligible roles, we offer discretionary incentive compensation which may be awarded in recognition of firm performance and individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company.
#J-18808-Ljbffr