Top Senior Level Data Science Jobs in Austin, TX

The Senior Data Scientist will focus on providing insights and analysis to optimize Babylist's fulfillment and operations, working closely with product and business leaders to improve processes and revenue generation through data-driven decisions.

The Senior Revenue Operations Analyst will manage sales incentives, analyze performance metrics, collaborate with teams to develop pricing strategies, maintain KPIs, and drive process improvements in a fast-paced environment.

As a Lead Analyst on the Growth Analytics team, you'll drive data-informed decision-making to accelerate customer growth. You will collaborate cross-functionally, conduct experiments, analyze funnels, and leverage statistical concepts to provide actionable insights that influence strategic decisions. Your expertise in advanced analytics will help identify growth opportunities and improve customer experiences.

The Senior Data Scientist develops models and performs analyses to improve business operations and support organizational goals. Responsibilities include managing data pipelines, statistical and machine learning models, and collaborating with data and business teams.

The Principal Data Scientist will design, enhance, and build advanced fraud detection solutions, utilizing machine learning and data mining techniques. Responsibilities include developing management information systems, collaborating with stakeholders on technical data problems, and mentoring team members. The role focuses on improving Visa's payment ecosystem and delivering insights for strategic initiatives.

The Sr. Data Scientist will analyze and improve user privacy and integrity initiatives through data insights and analytics. Responsibilities include developing dashboards, collaborating with product and engineering teams, performing data analysis, and creating A/B tests. The role focuses on safeguarding user privacy while supporting product initiatives.

The Data Scientist will be responsible for designing experiments, monitoring key metrics, analyzing dashboards, building data sets, and making proposals for future projects. The role involves exploratory data analysis, user behavior modeling, and maintaining data infrastructure using Spark and SQL for analyses and pipelines.