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 Chief Data & Analytics Office (CDAO) at JPMorgan Chase, you will have the unique opportunity to apply sophisticated machine learning methods to complex tasks. You will collaborate with various teams and actively participate in our knowledge sharing community. In this role, you will be part of a highly collaborative environment, working closely with our business, technologists, and control partners to deploy solutions into production. We are looking for someone with a strong passion for machine learning, who is motivated to invest time in learning, researching, and experimenting with new innovations in the field. If you have solid expertise in Deep Learning with hands-on implementation experience, strong analytical thinking, and a deep desire to learn, we would love to hear from you.
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 Or an MS with at least 3 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.
Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences. 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.
JPMorganChase, 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. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
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. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans.
Base Pay/Salary  Seattle, WA $128,250.00 - $195,000.00 / year; New York, NY $164,350.00 - $260,000.00 / year.

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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 Chief Data & Analytics Office (CDAO) at JPMorgan Chase, you will have the unique opportunity to apply sophisticated machine learning methods to complex tasks. You will collaborate with various teams and actively participate in our knowledge sharing community. In this role, you will be part of a highly collaborative environment, working closely with our business, technologists, and control partners to deploy solutions into production. We are looking for someone with a strong passion for machine learning, who is motivated to invest time in learning, researching, and experimenting with new innovations in the field. If you have solid expertise in Deep Learning with hands-on implementation experience, strong analytical thinking, and a deep desire to learn, we would love to hear from you.<h3>Job Responsibilities</h3><ol><li>Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community.</li><li>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.</li><li>Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production.</li><li>Drive Firm wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business.</li></ol><h3>Required qualifications, capabilities, and skills</h3><ol><li>PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science Or an MS with at least 3 years of industry or research experience in the field.</li><li>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.</li><li>Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas).</li><li>Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals.</li><li>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.</li><li>Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments.</li><li>Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences. Curious, hardworking and detail-oriented, and motivated by complex analytical problems.</li></ol><h3>Preferred qualifications, capabilities, and skills</h3><ol><li>Strong background in Mathematics and Statistics and familiarity with the financial services industries and continuous integration models and unit test development.</li><li>Knowledge in search/ranking, Reinforcement Learning or Meta Learning.</li><li>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.</li><li>Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal.</li></ol>JPMorganChase, 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. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.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. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans.<h3>Base Pay/Salary</h3>Seattle, WA $128,250.00 - $195,000.00 / year; New York, NY $164,350.00 - $260,000.00 / year.
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Are you passionate about machine learning and using Generative AI models to improve customer experience? That is what we, the Intelligent Agents team at Expedia, do. Our mission is to provide a platform that powers intelligent agent experiences (conversational and non-conversational) for Expedia customers with Generative AI being the core of it. The platform supports over 2M conversations per week.
What you will do:
Utilize SQL, Python, and other relevant tools to efficiently extract and merge data from diverse sources and create comprehensive datasets essential for building models and/or fine-tuning large language models.
Conduct exploratory data analysis to understand data distributions, trends, and potential challenges.
Fine-tune pre-existing Large Language Models (LLMs) to address specific business problems and domains.
Engage in prompt engineering, crafting tailored prompts and inputs to guide LLM outputs toward desired business outcomes.
Experiment with fine-tuning strategies, prompt designs, and domain-specific adaptations to optimize LLM performance for travel domain applications.
Work closely with stakeholders to understand business objectives, translate them into actionable tasks for LLM fine-tuning, and iterate on feedback-based solutions.
Contribute to developing innovative approaches for leveraging LLMs to solve business challenges, driving value and impact for the organization.
Document experimental procedures, findings, and results clearly and organized.
Communicate progress, challenges, and proposed solutions effectively to team members and stakeholders.
Give feedback to other MLS in the team meetings and help them with technical discussions.
Stay updated with the latest research papers, techniques, and best practices in the field of LLMs and related areas, and lead regular meet-ups with other MLSs in the team to discuss them.
Develop an understanding of ethical considerations related to LLMs, including bias, fairness, privacy, and misinformation issues.
Collaborate effectively with team members from diverse backgrounds, including product managers, engineers, and domain experts.
Who you are:
Experience: 7+ years for Bachelor's OR 5+ years for Master's OR 4+ years for PhD.
Learned experience across a wide range of technologies and algorithms with strong algorithm design and object-oriented programming skills in at least one of the major programming languages like Java, C/C++, Python.
Working knowledge of Generative AI and AI ethics.
Built and maintained multiple data science projects/products in production environments.
Participated in the technical community, including blog posts, tech talks, open source contributions, or data mining competitions.
Vocal with opinions and energized by new ideas, keen to educate others with excellent written and verbal communication.
The total cash range for this position in Seattle is $173,000.00 to $242,500.00. Employees in this role have the potential to increase their pay up to $277,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.
Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future.
Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical/dental/vision, paid time off, and an Employee Assistance Program. To fuel each employee’s passion for travel, we offer a wellness & travel reimbursement, travel discounts, and an International Airlines Travel Agent (IATAN) membership. View our full list of benefits.
About Expedia Group
Expedia Group (NASDAQ: EXPE) powers travel for everyone, everywhere through our global platform. Driven by the core belief that travel is a force for good, we help people experience the world in new ways and build lasting connections. We provide industry-leading technology solutions to fuel partner growth and success, while facilitating memorable experiences for travelers. Expedia Group's family of brands includes: Brand Expedia, Hotels.com, Expedia Partner Solutions, Vrbo, trivago, Orbitz, Travelocity, Hotwire, Wotif, ebookers, CheapTickets, Expedia Group Media Solutions, Expedia Local Expert, CarRentals.com, and Expedia Cruises.
Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.

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Join the Chief Data & Analytics Office (CDAO) at JPMorgan Chase, a team dedicated to accelerating the firm's data and analytics journey, ensuring data quality, and leveraging it to promote decision-making. We're offering opportunities at Sr. Associate, Vice President, and Executive Director levels in New York, where you'll apply sophisticated machine learning methods to optimize business decisions across various banking applications. With your expertise, you'll shape mission-critical solutions using intelligent algorithms.As a Machine Learning Scientist - Time Series and Reinforcement Learning - Machine Learning Center of Excellence in the Time Series and Reinforcement Learning group, you will have the unique opportunity to apply sophisticated machine learning methods to various banking applications. You will be at the forefront of developing scalable tools leveraging machine learning and deep learning models to solve real-world problems related to finance, economics, and operations of JP Morgan. You will also have the chance to collaborate with all lines of businesses within JPMorgan Chase, leading your own project from conception to deployment of a production-level machine learning application.Job Responsibilities<ul><li>Develop scalable tools leveraging machine learning and deep learning models to solve real-world problems for various problems related to finance, economics, and operations of JP Morgan.</li><li>Collaborate with all of JPMorgan Chase's lines of businesses, such as Investment Bank, Commercial Bank, and Asset Management.</li><li>Lead your own project. Suggest, collect and synthesize requirements. Create an effective roadmap towards the deployment of a production-level machine learning application.</li></ul>Required qualifications, capabilities, and skills<ul><li>PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Operations Research, Data Science.</li><li>For VP position, minimum 3 years of working experience.</li><li>Experience in machine learning project development.</li><li>Knowledge of machine learning/data science theory, techniques, and tools.</li><li>Scientific thinking, ability to work with literature, and the ability to implement complex projects.</li><li>Ability to understand business problems, study literature for a solution approach, write high-quality code for the chosen method, design training and experimentation to validate the algorithms and implementation, and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals.</li><li>Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.</li><li>Curious, hardworking, detail-oriented, and motivated by complex analytical problems.</li></ul>Preferred qualifications, capabilities, and skills<ul><li>Solid time series analysis, speech recognition, NLP or financial engineering background.</li><li>Strong background in Mathematics and Statistics.</li><li>Published research in areas of Machine Learning, Deep Learning, or Reinforcement Learning at a major conference or journal.</li><li>Experience with GPUs and cloud-based training of deep neural networks.</li><li>Contribution to open-source projects on Machine Learning.</li><li>Knowledge in Reinforcement Learning or Meta Learning.</li><li>Experience with big-data technologies such as Hadoop, Spark, SparkML, etc.</li></ul>Base Pay/Salary Palo Alto, CA $164,350.00 - $260,000.00 / year; Seattle, WA $164,350.00 - $260,000.00 / year; New York, NY $164,350.00 - $260,000.00 / year.
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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.
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 or an MS with at least 3 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.
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. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law.
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Are you passionate about machine learning and using Generative AI models to improve customer experience? That is what we, the Intelligent Agents team at Expedia, do. Our mission is to provide a platform that powers intelligent agent experiences (conversational and non-conversational) for Expedia customers with Generative AI being the core of it. The platform supports over 2M conversations per week.What you will do:<ol><li>Utilize SQL, Python, and other relevant tools to efficiently extract and merge data from diverse sources and create comprehensive datasets essential for building models and/or fine-tuning large language models.</li><li>Conduct exploratory data analysis to understand data distributions, trends, and potential challenges.</li><li>Fine-tune pre-existing Large Language Models (LLMs) to address specific business problems and domains.</li><li>Engage in prompt engineering, crafting tailored prompts and inputs to guide LLM outputs toward desired business outcomes.</li><li>Experiment with fine-tuning strategies, prompt designs, and domain-specific adaptations to optimize LLM performance for travel domain applications.</li><li>Work closely with stakeholders to understand business objectives, translate them into actionable tasks for LLM fine-tuning, and iterate on feedback-based solutions.</li><li>Contribute to developing innovative approaches for leveraging LLMs to solve business challenges, driving value and impact for the organization.</li><li>Document experimental procedures, findings, and results clearly and organized.</li><li>Communicate progress, challenges, and proposed solutions effectively to team members and stakeholders.</li><li>Give feedback to other MLS in the team meetings and help them with technical discussions.</li><li>Stay updated with the latest research papers, techniques, and best practices in the field of LLMs and related areas, and lead regular meet-ups with other MLSs in the team to discuss them.</li><li>Develop an understanding of ethical considerations related to LLMs, including bias, fairness, privacy, and misinformation issues.</li><li>Collaborate effectively with team members from diverse backgrounds, including product managers, engineers, and domain experts.</li></ol>Who you are:<ol><li>Experience: 7+ years for Bachelor's OR 5+ years for Master's OR 4+ years for PhD.</li><li>Learned experience across a wide range of technologies and algorithms with strong algorithm design and object-oriented programming skills in at least one of the major programming languages like Java, C/C++, Python.</li><li>Working knowledge of Generative AI and AI ethics.</li><li>Built and maintained multiple data science projects/products in production environments.</li><li>Participated in the technical community, including blog posts, tech talks, open source contributions, or data mining competitions.</li><li>Vocal with opinions and energized by new ideas, keen to educate others with excellent written and verbal communication.</li></ol>The total cash range for this position in Seattle is $173,000.00 to $242,500.00. Employees in this role have the potential to increase their pay up to $277,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future.Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical/dental/vision, paid time off, and an Employee Assistance Program. To fuel each employee’s passion for travel, we offer a wellness & travel reimbursement, travel discounts, and an International Airlines Travel Agent (IATAN) membership. View our full list of benefits.About Expedia GroupExpedia Group (NASDAQ: EXPE) powers travel for everyone, everywhere through our global platform. Driven by the core belief that travel is a force for good, we help people experience the world in new ways and build lasting connections. We provide industry-leading technology solutions to fuel partner growth and success, while facilitating memorable experiences for travelers. Expedia Group's family of brands includes: Brand Expedia, Hotels.com, Expedia Partner Solutions, Vrbo, trivago, Orbitz, Travelocity, Hotwire, Wotif, ebookers, CheapTickets, Expedia Group Media Solutions, Expedia Local Expert, CarRentals.com, and Expedia Cruises.Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.
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Join the Chief Data & Analytics Office (CDAO) at JPMorgan Chase, a team dedicated to accelerating the firm's data and analytics journey, ensuring data quality, and leveraging it to promote decision-making. We're offering opportunities at Sr. Associate, Vice President, and Executive Director levels in New York, where you'll apply sophisticated machine learning methods to optimize business decisions across various banking applications. With your expertise, you'll shape mission-critical solutions using intelligent algorithms. As a Machine Learning Scientist - Time Series and Reinforcement Learning - Machine Learning Center of Excellence in the Time Series and Reinforcement Learning group, you will have the unique opportunity to apply sophisticated machine learning methods to various banking applications. You will be at the forefront of developing scalable tools leveraging machine learning and deep learning models to solve real-world problems related to finance, economics, and operations of JP Morgan. You will also have the chance to collaborate with all lines of businesses within JPMorgan Chase, leading your own project from conception to deployment of a production-level machine learning application. Job Responsibilities Develop scalable tools leveraging machine learning and deep learning models to solve real-world problems for various problems related to finance, economics and operations of JP Morgan. Collaborate with all of JPMorgan Chase's lines of businesses, such as Investment Bank, Commercial Bank, and Asset Management. Lead your own project. Suggest, collect and synthesize requirements. Create an effective roadmap towards the deployment of a production-level machine learning application. Required qualifications, capabilities, and skills PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Operations Research, Data Science For VP position, minimum 3 years of working experiences Experiences in machine learning project development Knowledge of machine learning / data science theory, techniques, and tools Scientific thinking, ability to work with literature and the ability to implement complex projects Ability to understand business problem, study literature for a solution approach, write high quality code for the chosen method, design training and experimentation to validate the algorithms and implementation, and to evaluate intrinsic and extrinsic metrics for model performance aligned with business goals Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences Curious, hardworking, detail-oriented and motivated by complex analytical problems Preferred qualifications, capabilities, and skills Solid time series analysis, speech recognition, NLP or financial engineering background. Strong background in Mathematics and Statistics. Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal. Experience with GPUs and cloud-based training of deep neural networks. Contribution to open-source projects on Machine Learning. Knowledge in Reinforcement Learning or Meta Learning. Experience with big-data technologies such as Hadoop, Spark, SparkML, etc #LI-ID1 JPMorgan Chase & Co., 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. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 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. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans Base Pay/Salary Palo Alto,CA $164,350.00 - $260,000.00 / year; Seattle,WA $164,350.00 - $260,000.00 / year; New York,NY $164,350.00 - $260,000.00 / year

Machine Learning Scientist Jobs in Seattle, WA

Machine Learning Scientist Nlp Senior Associate Machine Learning Center Of Excellence
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Machine Learning Scientist Nlp Senior Associate Machine Learning Center Of Excellence
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Senior Machine Learning Scientist
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Machine Learning Scientist Time Series And Reinforcement Learning Machine Learning Center O
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Machine Learning Scientist Natural Language Processing Nlp Sr Associate R
December 10, 2024

Senior Machine Learning Scientist
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Machine Learning Scientist Time Series And Reinforcement Learning Machine Learning Center Of Excellence
December 6, 2024

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Machine Learning Scientist Jobs in Seattle, WA

Machine Learning Scientist Nlp Senior Associate Machine Learning Center Of ExcellenceDecember 18, 2024

Machine Learning Scientist Nlp Senior Associate Machine Learning Center Of ExcellenceDecember 17, 2024

Senior Machine Learning ScientistDecember 11, 2024

Machine Learning Scientist Time Series And Reinforcement Learning Machine Learning Center ODecember 10, 2024

Machine Learning Scientist Natural Language Processing Nlp Sr Associate RDecember 10, 2024

Senior Machine Learning ScientistDecember 9, 2024

Machine Learning Scientist Time Series And Reinforcement Learning Machine Learning Center Of ExcellenceDecember 6, 2024