Top Data & Analytics Jobs

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.

Lead Data Scientist responsible for guiding projects, mentoring a team, developing data-driven solutions, and collaborating across departments to drive insights.

Run and analyze product experiments, define product metrics and telemetry for web and mobile, build funnel/retention/cohort analyses using SQL and Python on Snowflake, maintain Omni dashboards, create AI-agent workflows to automate routine analysis, and translate findings into clear product recommendations alongside PMs, designers, and engineers.

Perform quantitative research and data analysis using private markets data to build models, indices, and analytics products. Maintain and enhance databases and internal models, support index rebalancing, respond to ad-hoc data requests, and collaborate with product, sales, and marketing to create data-driven content and insights for clients and stakeholders.

The Data Engineer will help build modern data infrastructure, designing ETL pipelines, modeling datasets, and collaborating with teams for improved data quality and accessibility.

The Staff Data Engineer will lead design and implementation of analytics platforms and data products, collaborate cross-functionally, mentor engineers, and drive best practices at Upside.

As a Mid-level Applied AI Data Scientist, you will apply statistical methods and machine learning to derive business insights from data and create Tableau visualizations.

The Programmatic Analyst will support campaign pricing and audience targeting strategies, analyze performance data, and collaborate with sales and operations teams to enhance campaign effectiveness.

The Data Engineer will design and build scalable data systems, contribute to the architecture of the data platform, and collaborate with AI/ML engineers to enhance automation and intelligence in Canoe's systems.

In this role, you'll build and scale high-throughput data pipelines, ensure data quality, and leverage AI for improved data operations. You'll also lead initiatives in a fast-paced environment focused on real estate data engineering.