Top Data & Analytics Jobs
As a Senior Machine Learning Engineer at Affirm, you will develop machine learning models for assessing creditworthiness, build training and monitoring systems, and collaborate with product and engineering teams. You'll implement data pipelines and drive innovations in credit decisioning with cutting-edge technologies.
The Machine Learning Infra Engineer will bridge the gap between data science and production systems by optimizing models for runtime performance, designing scalable MLOps pipelines, and implementing monitoring frameworks. They will work closely with data scientists to improve workflows and ensure reliability across the system, while also developing data versioning and deployment strategies.
As a Staff Machine Learning Ops Engineer at Grubhub, you will architect and develop scalable MLOps pipelines, oversee monorepo management, implement monitoring frameworks, drive platform improvements, enhance engineering standards, and establish processes for data lineage and model management.
.jpg)
The Senior Machine Learning Engineer will develop innovative pricing algorithms, navigate complex datasets, and lead models from conception to production while collaborating with cross-functional teams in a fast-paced environment.
As a Staff Machine Learning Engineer, you will lead the design and development of Generative AI solutions for Firefox, focusing on building infrastructure and ensuring model performance and reliability. This role involves collaborating with cross-functional teams and mentoring junior engineers.
As a Staff Data Engineer, you will lead the design, development, and maintenance of data infrastructure and pipelines, ensuring efficient access to data for business intelligence and analytical needs. You will mentor junior engineers while overseeing data integration projects and driving the technical vision of the department, ensuring alignment with Zoro's strategic goals.
The Sr. Data Scientist at Empower is responsible for the entire model development process, including creating and enhancing credit risk models, partnering with various teams to implement solutions, and driving business growth through data-driven insights.
The Principal Data Scientist will develop innovative machine learning models and build a data-driven culture that enhances customer financial inclusion. Responsibilities include feature engineering, collaborating with teams to adopt models, and establishing data science standards. The role entails solving high-impact challenges related to marketing, product development, and user experience personalization while monitoring and updating production models.
Featured Jobs
The Senior Machine Learning Engineer will design and implement machine learning applications, collaborate with cross-functional teams, optimize data pipelines, and ensure high availability of ML systems. Responsibilities include building ML models, automating tests and deployments, and monitoring production models while following best practices in AI.
As a Staff Machine Learning Engineer at Handshake, you will lead a small team to enhance AI products and infrastructure, focusing on Generative AI and Recommendations. You will develop machine learning systems, design partnerships across teams, and drive technical direction while ensuring high-quality execution and user-centered solutions.
As a Machine Learning Engineer II, you will develop and deploy machine learning solutions for inventory optimization, collaborating with data scientists and automating data processes. Your role involves creating scalable data analyses, managing ETL pipelines, and exploring innovative technologies to enhance our analytics capabilities.
As a Machine Learning Engineer at Kalepa, you will lead the development and deployment of machine learning models to gauge business risks, utilizing diverse data sources. You'll have full project ownership and collaborate closely with Product Management and Software Engineering teams in an agile environment.
As Sr. Director of Data, Analytics, and AI at NinjaTrader, you will lead efforts in data infrastructure, data science, business intelligence, machine learning, and AI. Your role involves managing a team, executing the technical roadmap, ensuring data governance, and fostering collaborations across departments to support data-driven decision-making and enhance user experience.
As a Senior Machine Learning Engineer, you will lead the development and deployment of machine learning models to analyze risk across various business classes, utilizing extensive structured and unstructured data. You will work closely with Product Management and Software Engineers within an agile environment to drive project ownership and direction.
As a Machine Learning Engineer II on the ML Fraud team at Affirm, you will develop models to predict fraud likelihood using proprietary and third-party data. You will collaborate across teams to improve fraud detection capabilities, implement data pipelines, and create innovative solutions for emerging fraud patterns, impacting financial performance significantly.
As a Perception Software Engineer at Zipline, you will be responsible for developing and implementing innovative perception systems for autonomous aircraft. This includes selecting sensor configurations, designing algorithms for object perception and avoidance, building software infrastructure to improve algorithms, and collaborating with various teams for effective decision-making processes.
As a Senior Machine Learning Engineer, you will design data pipelines, develop machine learning models, and collaborate with various teams to integrate ML capabilities into products. You will also train others, conduct experiments to validate outcomes, and serve as a thought leader in data-driven innovations.
As a Senior Machine Learning Engineer, you'll lead the development and deployment of machine learning models to analyze business risks. You'll handle structured and unstructured data to derive insights and work closely with product and software teams while managing your project ownership.
As a Machine Learning Engineer at Kalepa, you will lead the development and deployment of machine learning models to assess risk across various business classes. You will convert large volumes of structured and unstructured data into actionable insights, working closely with Product Management and Software Engineers over two-week sprints.
As a Machine Learning Engineer, you will lead the development and deployment of machine learning models to assess the risk of various businesses by analyzing structured and unstructured data from multiple sources, including web data and satellite imaging.
Lead AI/ML Scientist role at Datasite, leading AI/ML projects from conception to implementation, optimizing AI models, and collaborating with cross-functional teams to enhance product offerings and customer satisfaction.
The Machine Learning Engineer will lead the development and deployment of machine learning models to assess the risk of various business classes. Responsibilities include analyzing structured and unstructured data to derive insights and ensuring project ownership and direction within a two-week sprint cycle.
As a Senior Machine Learning Engineer, you will lead the development and deployment of machine learning models to assess business risk, utilizing both structured and unstructured data. You will work closely with Product Management and Software Engineers in an agile environment, taking ownership of your projects to drive their direction and execution.
The Senior Machine Learning Engineer at Kalepa will lead the development and deployment of machine learning models to assess business risk using structured and unstructured data. Responsibilities include project ownership, collaboration with product managers and software engineers, and working within a two-week sprint cycle.
The Senior Machine Learning Engineer will lead the development and deployment of machine learning models to analyze business risks. This role requires turning large volumes of structured and unstructured data into actionable insights while managing project direction and collaborating with teams on a two-week sprint cycle.
All Filters
No Results
No Results
