Top Hybrid Data Science Jobs

The Principal Data Scientist will lead analytics strategies, drive execution, mentor junior scientists, and innovate analytical practices for business decisions.

As a Lead Data Scientist, you will develop ML/AI solutions, collaborate with teams, present insights, and manage data projects to enhance business operations.

As a Senior Associate Data Scientist, you'll develop AI and software engineering solutions by collaborating with cross-functional teams, leveraging advanced technologies to analyze large datasets and build machine learning models.

Lead development of a greenfield data product by partnering with customers and product teams to build analytics and models (simulation, Bayesian networks, optimization, ML). Maintain existing analytics, improve predictive churn models, and translate customer needs into production-grade SQL/dbt pipelines, dashboards, and data-driven product features.

The role involves researching, designing, and implementing analytical methodologies for performance tools in mining operations, collaborating with cross-functional teams to enhance decision making through robust data analysis and frameworks.

The Data Science Manager will lead analytics and engineering functions, implement ML solutions, and engage with marketing leadership to drive growth strategies. Responsibilities include managing projects, optimizing models, and fostering talent development.

The Senior Data Scientist will lead the development of personalization algorithms, collaborate cross-functionally, build data pipelines, and optimize machine learning models.

As a Data Scientist at Opendoor, you will build pricing models and frameworks, run experiments, and collaborate with teams to enhance pricing accuracy and business strategy.

The Staff Data Scientist will drive business strategy through predictive insights, collaborate across teams, and develop solutions to enhance products and reduce losses.

The Data Scientist will collaborate with various teams, run experiments, analyze data to inform product strategy, and drive growth through advanced analytics and machine learning.