Top Senior Level Data Science Jobs in Dallas, TX

As a Principal Data Scientist, you will develop machine learning models for hotel demand and pricing prediction, optimize revenue through pricing strategies, and lead technical projects. Collaboration with product and engineering teams is key to integrating solutions and presenting findings to management.

As a Staff Data Scientist at Enigma, you will leverage machine learning and statistical methods to enhance data accuracy and usability. You will work within cross-functional teams, develop innovative solutions, validate results against real-world data, and contribute to critical product developments that impact small businesses' access to financial services.

The Senior Revenue Operations Analyst will lead analytics projects that inform decision-making across Go-To-Market functions. Responsibilities include coordinating cross-department initiatives, improving analytics processes, ensuring data integrity, and conducting analyses to support revenue operations.

The Senior Data Scientist will analyze resident health and care data to provide insights and feedback, design and maintain algorithms, integrate new datasets, create visualizations, and collaborate with various teams to address business needs using data.

The Sr. Principal Data Scientist at Northrop Grumman is responsible for creating data mining architectures, statistical reporting, and data analysis methodologies to identify trends in large datasets. This role requires strong statistical skills, familiarity with data science toolkits, and deep learning frameworks to provide insights for business challenges.

As a Sr. Data Scientist, you will lead the development of advanced scoring and indexing models for predicting business outcomes, collaborate with teams to integrate solutions, conduct data analysis, and ensure the accuracy of models while communicating insights to stakeholders.

As a Senior Data Scientist at Entefy, you will influence the future of productivity through advanced analytics. Responsibilities include delivering insights from structured and unstructured datasets, leading other data scientists, and employing strong data visualization skills.