Top Data & Analytics Jobs

Design and develop machine learning systems, preprocess and engineer features, research and implement machine learning algorithms, support tools for machine learning experiments, transform data science prototypes into machine learning models, develop applications based on business requirements.

As a Summer Associate at the Machine Learning Center of Excellence, you will use advanced machine learning techniques in areas like NLP and reinforcement learning. Your role involves collaborating with mentors to solve business challenges and enhance organizational operations, requiring expertise in machine learning, deep learning, and statistical methods.

The role involves conducting research in computer vision and machine learning, providing innovative solutions to internal project teams, documenting findings in scientific papers, and contributing to intellectual property protections.

Develop state-of-the-art machine learning models for NLP, speech analytics, and recommendation systems. Collaborate with various teams to deploy solutions into production and drive successful outcomes. Stay updated on the latest advancements in NLP concepts and machine learning techniques.

As a Senior Internal Audit Associate, you'll conduct audits focusing on risk assessment, control identification, and continuous monitoring for the Chief Data & Analytics Office. This role involves evaluating control effectiveness, communicating findings, and driving efficiency in audit processes through technology. Collaboration with stakeholders and staying updated on industry developments are key responsibilities.

The Director of Architecture for AI/ML drives the adoption of machine learning technologies, collaborates with stakeholders to frame business problems, establishes data engineering processes, and provides technical leadership throughout the machine learning lifecycle, developing end-to-end AI/ML solutions.

As a Machine Learning Scientist - NLP, you will leverage machine learning and deep learning techniques to solve complex problems in natural language processing and more. You will collaborate with various teams to deploy solutions in production, research new methods, and develop scalable models for real-world applications.

Applied AI/ML Senior Associate role at JPMorgan Chase & Co. Responsibilities include developing AI/ML solutions, collaborating with teams, and advising on optimal solutions. Required qualifications include advanced degree in analytical field, experience in AI/ML, NLP, and strong coding skills in Python.

As a Staff Machine Learning Engineer in the Risk team at Cash App, you'll develop ML solutions to mitigate risk and fraud while collaborating cross-functionally with various teams. You'll utilize your expertise in machine learning algorithms and data analysis to enhance product lifecycle management.

As a Senior Machine Learning Engineer, you will leverage your expertise to develop analytical and machine learning solutions focused on mitigating risk and fraud for Cash App. You'll collaborate with cross-functional teams to balance financial loss, regulatory risks, and enhance customer experiences, deploying updates regularly based on data-driven insights.

Design, build, and maintain Machine Learning systems to flag fraudulent activities in real-time. Collaborate with global colleagues on challenging technical problems. Lead the conception and implementation of large-scale experiments to validate novel ideas. Apply latest theoretical advancements to enhance existing products and technologies. Conduct experiments across various computer science domains.

As a Senior Machine Learning Engineer in Personalization, you'll design and manage distributed services and tools for machine learning applications, lead projects across engineering boundaries, and collaborate with various teams. Your role includes building recommendation and ranking systems while ensuring high code quality and providing mentorship to teammates.

Apply sophisticated machine learning methods in the Time Series and Reinforcement Learning group at JPMorgan Chase. Develop scalable tools for real-world problems in finance and operations, collaborating with various lines of business. Lead projects from conception to deployment of production-level machine learning applications.

As Vice President in the Machine Learning Scientist - NLP team, responsible for applying advanced ML techniques to tasks like NLP, speech analytics, time series, and recommendation systems. Collaborate with various teams, drive firm-wide initiatives, develop ML models, and contribute to knowledge sharing community. PhD in a quantitative discipline with 3 years of industry experience or MS with 5 years. Strong background in NLP, deep learning, machine learning toolkits, big data, and scalable model training. Experience in designing experiments, intrinsically evaluating model performance, and effective communication.

Machine Learning Scientist specializing in Natural Language Processing (NLP) at a senior associate level. Responsibilities include researching and implementing machine learning models, collaborating with cross-functional teams, and driving firm-wide initiatives. Required qualifications include a PhD in a quantitative discipline or an MS with 3 years of industry experience, expertise in NLP and deep learning, proficiency in machine learning toolkits, and strong communication skills.

Research, develop, and implement state-of-the-art machine learning models for NLP, speech recognition, time series predictions, and recommendation systems. Collaborate with various teams to deploy solutions and drive firm-wide initiatives. Independently study, research, and experiment with new innovations in machine learning.

As a Senior Associate Machine Learning Scientist, you will leverage advanced machine learning techniques to tackle challenges in natural language processing, speech analytics, time series, and recommendation systems. You will collaborate with multiple teams to develop and deploy machine learning models, while also engaging in research and knowledge sharing within the organization.