Data Scientist

Summary

Northbeam is building a marketing intelligence platform that uses attribution modeling, machine learning, and unified business data to help eCommerce brands measure and improve marketing performance. The Data Scientist will join the Applied Measurement team to solve customer marketing measurement problems, analyze experiments and models, build scalable diagnostic tools, and communicate statistical insights and recommendations to clients.

Responsibilities

• Partner with customers and internal teams to understand important 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 more complex methodological and modeling problems. Collaborate with cross-functional peers to support clients with the practical application
• Identify recurring challenges and opportunities to improve our models, diagnostics, tooling, and processes
• Build reusable analysis and diagnostic tools that make measurement more reliable and scalable
• As you grow in the role, contribute to the development of new methodologies, models, and production measurement capabilities

Skills

• Bachelor's degree
• In Computer Science, Statistics, Mathematics, Engineering, or another highly quantitative field
• 2+ years of experience building and deploying data science, machine learning, or AI systems in production
• Strong foundation in statistics, machine learning, experimentation, and causal inference
• Excellent verbal and written communication skills
• Strong coding and debugging skills
• The ability to write production-quality code and diagnose issues across the full stack, including source data, pipelines, model logic, and customer-facing outputs
• A service-oriented mindset
• Comfortable working in a fast-paced startup environment and driving projects from concept to production with a high degree of autonomy
• Growth mindset, intellectual curiosity, and a willingness to learn new domains, customer verticals, and measurement methodologies
• MS
• Ideally including direct client- or customer-facing work
• Genuine enthusiasm for explaining these methods to non-technical audiences
• Comfortable leading a customer conversation, explaining a modeling tradeoff to a non-technical stakeholder, and writing up findings clearly
• Energized by direct, hands-on customer problem-solving, not only methodology for its own sake
• Strong preference for candidates with a robust statistical background and prior experience in digital marketing or eCommerce analytics

Qualifications

Must Haves

• Bachelor's degree
• in Computer Science, Statistics, Mathematics, Engineering, or another highly quantitative field
• 2+ years of experience building and deploying data science, machine learning, or AI systems in production
• Strong foundation in statistics, machine learning, experimentation, and causal inference
• Excellent verbal and written communication skills
• Strong coding and debugging skills
• the ability to write production-quality code and diagnose issues across the full stack, including source data, pipelines, model logic, and customer-facing outputs
• A service-oriented mindset
• Comfortable working in a fast-paced startup environment and driving projects from concept to production with a high degree of autonomy
• Growth mindset, intellectual curiosity, and a willingness to learn new domains, customer verticals, and measurement methodologies

Nice to Haves

• MS
• ideally including direct client- or customer-facing work
• genuine enthusiasm for explaining these methods to non-technical audiences
• comfortable leading a customer conversation, explaining a modeling tradeoff to a non-technical stakeholder, and writing up findings clearly
• energized by direct, hands-on customer problem-solving, not only methodology for its own sake
• Strong preference for candidates with a robust statistical background and prior experience in digital marketing or eCommerce analytics

Benefits

• An equity package
• Comprehensive healthcare benefits (medical, dental, and vision)
• A 401(k) plan
• A flexible PTO policy
• 12 company-paid holidays
• 12 weeks of paid parental leave
• A $500 work-from-home stipend to support your remote setup
• Remote-friendly work arrangement