Top Remote Senior Level Data Science Jobs in Las Vegas, NV

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 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.

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.

The Senior Revenue Operations Analyst will focus on territory management and automation processes within the Revenue Operations team. Responsibilities include analyzing data to provide territory recommendations, systematizing territory assignments, and ensuring data hygiene across various teams. Collaboration with Customer Success and GTM teams is essential to enhance lead distribution and territory alignment.

The Senior Revenue Operations Analyst will shape and assign sales territories through data analysis and automation, collaborate cross-functionally, and monitor data accuracy. Responsibilities include improving internal processes, utilizing tools like Dunn & Bradstreet, and providing guidance to the GTM teams.

Responsible for developing tailored data science solutions, leveraging machine learning techniques to transform complex datasets into actionable insights, communicating findings, designing scalable models, and working cross-functionally with teams to integrate data science solutions.