Top Hybrid Data Science Jobs

Lead data science and analytics for user growth, managing a team, driving business intelligence, and influencing product strategy based on data insights.

The Senior AI/ML Data Scientist drives strategic data initiatives, designs advanced predictive models, analyzes large datasets, and mentors other data scientists while collaborating cross-functionally to influence product design and implementation.

As a Senior Data Scientist, you will build predictive models for credit decisioning, analyze portfolio performance, and collaborate with teams to optimize loan strategies. This role focuses on driving credit quality and loss performance within the lending lifecycle.

Lead end-to-end data science projects to enhance Parafin's underwriting engine by developing predictive models, optimizing pricing, and collaborating with engineering teams.

As a Senior Data Scientist, you will lead modeling initiatives, build forecasting systems, and mentor team members while collaborating with Finance, Product, and Sales teams.

As an Applied Data Scientist, you will develop credit models and predictive systems for Clair’s products, utilizing machine learning and statistical modeling while collaborating with cross-functional teams to optimize credit decisions.

As a Senior Business Intelligence Analyst, you will leverage data to provide insights, improve field performance, and support strategic decision-making.

As a Data Scientist, you will analyze complex data sets, build machine learning models, and work in a team to provide solutions, ensuring data security and optimization.

The Director of Data Strategy will develop and execute a data strategy, ensuring data quality and governance across the organization, fostering collaboration among various departments for improved analytics and business outcomes.

Lead design and deployment of graph ML and network-biology analyses to generate drug target hypotheses from RWD and multi-omic data. Prototype methods, integrate solutions with engineers, prioritize tasks, and communicate results to cross-functional stakeholders while championing data science best practices.