You'll play a key role in shaping our products and decisions by working across product, engineering, and commercial teams to ensure data is at the center of everything we do. Mine and analyze large datasets to inform product development, marketing strategies, and business processes. Build predictive models that optimize customer experiences, operational efficiency, and revenue growth.
In this role, you will support two large engineering organizations by managing end-to-end headcount processes, driving data accuracy, and delivering insights that inform workforce planning and operational decisions. You will work closely with senior leaders to maintain clean organizational structures, partner on hiring-related initiatives, and build/maintain reporting dashboards that support business operations at scale.
Enhance search engine results as an evaluator. Provide feedback on text, audio, images, and videos to refine AI data used by major search engines, social media sites, streaming platforms and more. Speak English proficiently (B2 level or higher) and reside in Japan. Commit to a minimum of 5 hours per week and have reliable internet.
Architect, build, and operate real-time/batch ETL pipelines, agentic orchestration flows, and AI/ML endpoints for autonomous, multi-agent production systems. Contribute actively to team processes, documentation, and operational quality. Build event-driven data workflows, integrate with various connectors, and expose agentic features.
Build a high-impact Talent Pool for advanced analytics, AI, and enterprise data platforms if you’re a LATAM-based Data Scientist with strong English. Solve complex problems using Python, R, SQL, Machine Learning, statistical modeling, forecasting, and cloud-based data ecosystems. The ideal candidate will have experience building predictive/prescriptive models, strong communication skills in English, and a passion for experimentation.
As a Data Systems Engineer at Northbeam, you will translate customer feedback into scalable data pipelines and products, creating, maintaining, and improving integrations and transformations in a complex network. The system is powered by data that spans numerous ad platforms and order management systems, requiring curiosity, experience, and a desire to build data pipelines and applications at scale.
The Senior Software Engineer - Data will architect, implement, and optimize data models, pipelines, and storage solutions across Acquisition.com’s data ecosystem, ensuring reliability, performance, and accessibility of data. This individual will serve as a bridge between raw information and actionable business intelligence, taking complex data initiatives from concept to delivery.
As a Data Scientist on Plaid’s Fraud Data team, you will analyze customer and network traffic to understand how Protect performs across different segments and use cases. You’ll build dashboards and performance metrics that create a clear, shared view of product health for both the team and our go-to-market partners.
The Data Engineering team is focused on the design, development, and support for 'all things data' at OppFi. This includes the deployment of Postgres databases which support our applications, our Snowflake Data Warehouse and multiple Airflow and Hevo ETLs. You will work on Postgresql Database Administration and Data Engineering.
We’re hiring a Lead Product Scientist to help build our Product Analytics capabilities at Paddle. This role sits at the intersection of Product and Data — quantifying the impact of our product features through historical studies, setting up our experimentation culture, and enabling a cadence of reviewing feature performance.