Top Data Science Jobs

The Data Scientist Senior Consultant will lead data analytics projects, manage client relationships, and develop data solutions using various tools. They require a strong background in data science and communication skills.

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

The Staff Data Scientist will deliver advanced analytics and machine learning solutions, focusing on technical execution, collaborative problem-solving, and ensuring robust models in quality and engineering domains.

As a Data Scientist, you will own analytical projects that influence product decisions and marketing campaigns. You'll apply statistical methods and predictive modeling to enhance customer value and drive business outcomes, collaborating cross-functionally to integrate insights into strategies.

Partner with product engineering to design and analyze experiments, apply causal reasoning and statistical modeling to marketplace data, and drive data-informed product decisions across the engineering org.

The Expert Exploitation Specialist/Data Scientist is responsible for production management, data entry, digital product replication, and workflow automation to optimize data processes.

The Data Scientist will analyze customer health, conduct quantitative research, develop insights for teams, and inform strategy based on data analysis.

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.

Lead and own the data science function: design and build production ML systems (recommendation, forecasting, segmentation), develop configurable multi-tenant models, run rigorous experimentation and causal analyses, connect model outputs to business impact, set scientific standards, and hire and mentor a high-velocity data science team.

The Data Scientist will develop and implement scalable machine learning solutions to solve business problems, collaborating with cross-functional teams.

Design and implement quantitative analytics and machine learning solutions using structured and unstructured data. Collaborate with business and technical teams to develop analytics strategy, deploy models for customer behavior and market modeling, and standardize computational services while communicating results to non-technical stakeholders.

The job involves supporting data-driven initiatives, performing analyses, building data models, and collaborating with product teams to enhance user engagement and improve business outcomes.

The Data Scientist will analyze large datasets, design machine learning models, collaborate on data management, and present findings to stakeholders.

The Data Scientist will develop and maintain models for asset valuation and portfolio management, perform statistical analysis, enhance data capabilities, and work with various teams to solve complex business problems in real estate investment lending.

The Data Scientist will analyze data, create dashboards, support strategic initiatives, and contribute to predictive modeling and machine learning efforts.

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.

As a Data Scientist II, you will analyze complex data, develop statistical models, and create data visualizations to support internal clients and enhance analytics capabilities. You will collaborate with technical leads and stakeholders, ensuring data quality and accuracy in deliverables.

The Data Scientist will build models using statistical and machine learning techniques, conduct analyses, collaborate with teams, and improve model performance.

The Data Scientist will analyze data to improve business operations, build AI/ML tools, visualize insights, and mentor stakeholders in AI initiatives.

Lead data science strategy across underwriting, claims, reinsurance, and portfolio management. Own multi-quarter cross-functional initiatives, design experiments and causal analyses, build scalable models and metrics, create executive dashboards, influence leadership decisions, and mentor scientists to raise technical rigor and repeatability.

The Data Scientist will build predictive models, analyze complex datasets, collaborate with engineering teams, and enhance operational efficiency through data science solutions.

The Data Scientist II will develop and improve machine learning models for document verification, engaging in model diagnostics and optimization, and collaborating with cross-functional teams to meet performance requirements.

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

Embed with Product and Engineering to define success metrics, design measurement and experimentation frameworks, instrument and monitor launches, translate model-driven signals into decisions, and build repeatable decision loops to convert analysis into shipped changes.

As a Senior Quantitative Data Scientist, you will ensure data quality, apply analytical methods for evidence generation, and collaborate with cross-functional teams to meet data strategy and analytic priorities.