Top Software Data Science Jobs

The Senior Customer Data Scientist will develop and deliver AI solutions, enable customer adoption, engage stakeholders, and contribute to platform development in enterprise settings.

Create and review realistic, locale-specific mathematics tasks and scoring rubrics in the target language to evaluate AI systems. Score submissions for accuracy and regulatory alignment, produce gold-standard solutions, and provide expert feedback to improve AI performance in local mathematical contexts.

The Data Scientist role involves designing and deploying machine learning systems, prototyping AI agents, collaborating with product teams, and addressing business problems. Responsibilities include model building, data analysis, client collaboration, and contributing to AI tooling.

The Head of Data will lead the data organization, define the company-wide data strategy, ensure high-quality decision making, collaborate across teams, mentor leaders, and establish best practices in data governance and execution.

Own end-to-end data science and ML work for B2C customers: build recommendation, forecasting, segmentation, and activation models; design A/B tests and causal analyses; create configurable multi-tenant model architectures; extract signal from sparse/noisy data; partner with engineering to productionize models and deliver analyses that change business decisions.

The Senior ML Data Scientist will develop machine learning models to detect fraud, manage the data science lifecycle, and collaborate with teams on strategies.

The Senior Data Scientist at LiveRamp will develop and maintain measurement models, translating complex statistical methodologies into scalable production pipelines and collaborating with cross-functional teams to enhance data collaboration for ad tech applications.

Use machine learning, statistical analysis, and advanced analytics to build and operationalize models and insights that inform commercial strategy; collaborate with BI and data teams to improve reporting, measure model impact, and present results to stakeholders.

Lead end-to-end data projects: ingest and clean unstructured data, build predictive models, design experiments, create dashboards, operationalize ML with Product/Engineering, and improve data quality and governance.

The Senior Data Solutions Partner acts as a liaison between stakeholders and the Data & Engineering organization, prioritizing analytics, automation, and technology use cases while ensuring alignment and governance throughout project delivery.