Northbeam

Data Scientist

• Partner with customers and internal teams to understand marketing measurement questions and translate them into data science problems
• Work with real-world customer data to ensure it is reliable and appropriate for modeling and measurement
• Analyze model and experiment results, investigate unexpected outcomes, and identify potential data, modeling, or measurement issues
• Translate complex statistical and modeling results into clear insights and actionable recommendations
• Partner with Senior Data Scientists on complex methodological and modeling problems
• Collaborate with cross-functional peers across Media Strategy, Customer Success, Product, and Engineering to support clients
• Identify recurring challenges and opportunities to improve models, diagnostics, tooling, and processes
• Build reusable analysis and diagnostic tools that make measurement more reliable and scalable
• Contribute to new methodologies, models, and production measurement capabilities as the role develops
• Explain statistical methodology, diagnose measurement issues, and communicate experimentation results to clients

Backend Engineer

• Architect the incrementality product into a reliable, scalable experimentation platform
• Set the direction for near-real-time data ingestion and processing
• Define patterns for AI-powered workflows helping marketers evaluate performance and act on insights
• Lead connection-state systems and the partner ecosystem across data ingestion and exports
• Shape technical approaches in adjacent product areas such as role-based access control (RBAC)
• Take products from early traction to meaningful scale and set technical direction
• Partner with data scientists, product managers, and designers
• Conduct design reviews, mentor engineers, and raise delivery standards

Staff Software Engineer, Python

Data Engineer

• Own the architecture of the ingestion and integration platform, setting patterns for onboarding new data sources
• Define technical direction for event-driven and batch processing across the company
• Make build/buy and migration decisions
• Establish standards for observability, data freshness, and failure handling
• Lead design across data engineering, infrastructure, and product teams
• Provide design review, mentorship, and hands-on coding to elevate engineers
• Identify unscoped platform problems, advocate for solutions, and drive them to completion
• Work across integrations and transformations involving ad platforms, order management systems, and real-time event collection

Staff Software Engineer, Data Systems – Python

• Architect the incrementality product into a reliable, repeatable experimentation platform
• Set the direction for near-real-time ingestion and processing beyond batch workflows
• Define patterns for AI-powered workflows helping marketers evaluate performance and act on insights
• Lead connection-state systems and the partner ecosystem across data ingestion and exports
• Shape technical approaches in adjacent product areas such as role-based access control (RBAC)
• Take products from ambiguity through architecture to production and scale
• Partner with data scientists, product managers, and designers
• Conduct design reviews, mentor engineers, and raise the standard for shipped work

• Build and maintain data pipelines that ingest and transform data from a variety of sources, with an eye toward reliability and maintainability
• Develop and support APIs that enable secure, tenant-aware data integrations with external systems
• Work within event-driven and batch processing architectures to keep data fresh and consistent
• Contribute to API design and integration patterns supporting real-time and batch ingestion across authentication mechanisms such as OAuth and API keys
• Add monitoring and alerting for data freshness issues, failures, and performance problems
• Improve data flows and transformations, balancing cost, efficiency, and delivery speed in a cloud-native environment
• Partner with data engineering, infrastructure, and product teams to improve the integration platform and onboard new sources
• Work with product managers, product engineers, and business leaders to turn customer needs into reliable data pipelines and products

Software Engineer, Data Systems – Python

• Contribute to the incrementality product as it grows into a reliable experimentation platform
• Build near-real-time ingestion and processing capabilities beyond batch workflows
• Build AI-powered workflows that help marketers evaluate performance and act on insights
• Improve connection-state systems and extend the partner ecosystem across data ingestion and exports
• Work on product areas such as role-based access control (RBAC)
• Contribute to frontend work to deliver complete product experiences
• Implement backend services and frontend components for end-to-end features
• Collaborate with data scientists, product managers, designers, and senior engineers

Software Engineer, Python

• Build features end to end, spending roughly 70% of time on backend work and 20–30% on frontend
• Build new products and capabilities, including incrementality and experimentation-platform functionality
• Build near-real-time data ingestion and processing capabilities
• Build AI-powered workflows for marketers to evaluate performance and act on insights
• Improve connection-state systems and extend the partner ecosystem across data ingestion and exports
• Work on product areas such as role-based access control (RBAC)
• Contribute to frontend work to deliver complete product experiences
• Collaborate with data scientists, product managers, designers, and senior engineers