Top Data & Analytics Jobs

This role involves leading product releases at Metropolis by developing and executing robust testing and release plans. The Product Operations Manager will collaborate with Product Managers and cross-functional teams to drive product adoption, communicate updates, and assess product impact based on data and feedback.

As a Principal Machine Learning Engineer, you will lead the development of prediction or optimization engines for advertising platforms, driving innovation through AI and machine learning. Responsibilities include designing ad algorithm architecture, developing scalable data analysis methods, and collaborating with cross-functional teams.

The Lead Software Engineer will develop and enhance Disney's advertising machine learning platform, focusing on improving inventory forecasting, ad delivery, pricing, and targeting using AI. This role involves creating scalable solutions for data analysis and modeling while collaborating with researchers and balancing architectural considerations.

Lead the development and optimization of algorithms for personalization and recommendation systems at Disney, driving and enabling ML usage across multiple domains. Collaborate with stakeholders to identify new opportunities while maintaining robust production deployment and high system reliability.

The Machine Learning Engineer will lead the development and deployment of machine learning models to assess business risk by transforming large datasets into valuable insights. Responsibilities include ownership of projects, collaboration with product management and software engineers, and operating within a two-week sprint methodology.

As a Machine Learning Engineer, you will lead the development and deployment of machine learning models to assess risks for various businesses, utilizing structured and unstructured data sources. You will own projects and collaborate closely with Product Management and Software Engineers within a two-week sprint framework.

The Senior Machine Learning Engineer will lead the development and deployment of machine learning models to assess business risk. Responsibilities include handling large volumes of both structured and unstructured data to derive insights, with full ownership of projects in a fast-paced team environment.

Kalepa is seeking a Machine Learning Engineer to lead the development, framing, and deployment of machine learning models to analyze risk across different classes of businesses. Responsibilities include turning structured and unstructured data into insights and collaborating closely with Product Management and Software Engineers.

As an Application Engineer, you will oversee design and implementation of assigned products, manage risks, analyze and deploy new user stories, guide junior engineers, and enforce IT standards. Collaboration with various stakeholders is crucial for achieving team commitments and ensuring high reliability of solutions.

As a Senior Machine Learning Engineer, you will lead the development and deployment of machine learning models to assess risks for various businesses, utilizing structured and unstructured data. You will have ownership of projects and collaborate closely with Product Management and Software Engineers in a two-week sprint cycle.

As a Machine Learning Engineer at Kalepa, you will develop and deploy machine learning models to assess the risk associated with various businesses. You will utilize structured and unstructured data, work closely with Product Management and Software Engineers, and have full ownership over project direction in a sprint-based team environment.

As a Machine Learning Engineer at Kalepa, you will be responsible for leading the development and deployment of machine learning models to assess business risks. You will analyze large datasets from various sources to extract insights and are expected to own and drive your projects within a sprint-based framework in collaboration with Product Management and Software Engineers.

As a Machine Learning Engineer at Kalepa, you will lead the design, development, and deployment of machine learning models to evaluate business risks. Handling both structured and unstructured data, you'll generate insights and collaborate with product and software teams to drive project direction in a fast-paced environment.

The Machine Learning Engineer at Kalepa will develop and implement AI models to enhance the Copilot platform for underwriters. The role involves collaborating with cross-functional teams, utilizing data analysis, and applying machine learning techniques to solve complex problems in commercial insurance.

As a Senior Machine Learning Engineering Manager, you will lead the end-to-end machine learning lifecycle, from data collection to deployment. You'll implement novel techniques, mentor team members, and collaborate with cross-functional teams to ensure effective communication and innovation.

As a Senior Machine Learning Engineer, you will lead the development and deployment of machine learning models to assess business risk. You'll transform diverse data sources into meaningful insights, collaborating with Product Management and Software Engineers during bi-weekly sprints.

The Machine Learning Engineer at Kalepa will frame, develop, and deploy machine learning models to assess business risks. This role involves analyzing structured and unstructured data to generate insights, collaborating closely with product and software teams, and working autonomously on projects within two-week sprints.