Top Data Engineer Jobs

The Machine Learning Engineer at Liftoff will develop and train algorithms for real-time bidding, analyze inventory performance, and oversee experiments for optimization strategies. The role involves enhancing existing ML infrastructure, collaborating with engineering teams on data pipelines, and fostering a culture of engineering excellence.

The Manager of Data Acquisition at Strive Health will lead data acquisition strategies and manage a team of data associates to enhance kidney care. Responsibilities include strategy execution, team leadership, and improving acquisition processes for better patient outcomes.

As a Data Science Co-op at Jellyfish, you will help develop algorithms, create machine learning models, and analyze data to provide insights for engineering teams. You will collaborate with customers and contribute to marketing efforts while exploring applied mathematics and machine learning.

The role entails using data and technology to enhance marketing operations by generating insights. Responsibilities include data analysis using SQL and Python, building revenue optimization models, aligning marketing planning with corporate strategy, and defining KPIs for performance measurement.

As a Machine Learning Researcher at Citadel Securities, you will apply advanced machine learning and AI techniques to analyze datasets, back-test models, and document your findings. Your work will contribute to developing innovative trading strategies in a fast-paced environment.

As a Senior Applied Scientist at Chewy, you will lead the deployment of machine learning and data science to enhance shopping experiences, develop new models, and influence product and engineering strategies. You will mentor junior scientists and present research findings to business leaders.

The Strategy and Business Analytics Experienced Consultant will engage with Transaction Services advisors and client stakeholders to conduct technology M&A due diligence, assess existing data systems, formulate strategic investment summaries, and establish connections between business and data strategies. Responsibilities include creating recommendations, thought leadership, and driving business growth by identifying opportunities with clients.