Top Software Data Science Jobs

As the first Data Scientist, you will analyze user data and AI outputs to enhance content creation, define metrics, conduct A/B testing, and collaborate closely with cross-functional teams to improve product features.

Design realistic biological benchmarks and curate high-quality datasets to evaluate and train AI systems; analyze model failures, iterate on data and evaluation criteria, collaborate with ML researchers, and manage workflows and documentation across domain experts.

The Data Scientist II will work with sports tracking data to build models and analyses for NHL and NBA organizations, focusing on data transformation and metrics development.

As a Data Scientist, you will collaborate across teams to build data solutions, design data pipelines, develop statistical models, and create visualizations to support business decisions.

The Data Science Manager will lead and mentor a team of data scientists, drive data-driven decision-making across Stripe, and collaborate with various stakeholders. Responsibilities include managing projects, recruiting, and contributing to broader data science initiatives.

Unstructured is seeking professionals for future roles focused on AI/ML projects. Join their talent pool to be considered for impactful positions in unstructured data processing.

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

The role involves designing and developing data applications, working with large data sets, and requires expertise with various data processing technologies. Candidates should have strong analytical skills and experience in prototyping software applications.

Lead development and monitoring of statistical and predictive models for B2B credit and fraud risk, pricing, and profitability. Cleanse and analyze internal and external data, produce portfolio risk reports and KPIs, communicate insights to executives, support Engineering/Product and data scientists, and build a consistent Model Development Framework.

Lead end-to-end data science projects including predictive modeling, algorithm design, and data pipelines. Build campaign-focused models (turnout, partisanship), perform exploration and visualization, translate insights into memos/presentations, collaborate with engineering to productionize models, mentor junior data scientists, and prototype emerging AI solutions for product impact.