Top Remote Data & Analytics Jobs in Houston, TX

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.

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 Senior Analyst is responsible for monitoring unusual banking transactions, using software tools to detect suspicious activity, reaching out to customers for clarification, and documenting findings. This role involves analyzing data patterns, conducting investigations, and adhering to compliance standards.

As the Director of Data Science and Analytics at Mixbook, you will lead the analytics team, develop statistical models, oversee business analysis, and implement data-driven strategies to enhance business performance and growth in a fully remote environment.

The Revenue Operations Senior Analyst will manage pipeline reporting and forecasting, design compensation plans, conduct data analysis, and collaborate with sales teams to enhance operational efficiency. Responsibilities include maintaining reports, supporting sales enablement, and optimizing processes through automation.

The Customer Experience Analyst investigates and resolves internal customer complaints through various channels, identifies trends in complaints, and develops action plans for compliance issues. They handle a minimum of 35 cases daily, improve complaint management processes, and create reports to help enhance overall complaint handling efficiency.

The Senior Data Analyst at Doximity will analyze extensive datasets to identify patterns among medical professionals and create analytics for products and clients. They will inform data team strategies, collaborate on data projects, and utilize statistical concepts, SQL, and Python for data analysis and visualization.