Staff Data Scientist (Marketing)

Join Asana, a leading work management platform, as a Staff Data Scientist in Marketing. In this role, you will be the technical expert responsible for using data and scientific techniques to enhance Asana's marketing effectiveness. You will drive the technical roadmap for data science, collaborate with marketing leadership, and provide technical leadership and mentorship to a team of data scientists. This position is based in San Francisco with a hybrid work schedule.

• Architect, design, and lead the technical execution for the Marketing Data Science roadmap, serving as the Solution Architect for all core projects including Media Mix Modeling (MMM), User Lifetime Value, Causal Inferences, Multi-touch Attribution, and Spend Optimization engines.
• Act as the primary technical subject matter expert for the Marketing Data Science team, setting the technical bar for modeling quality, code rigor, data pipeline architecture, and solution scalability.
• Collaborate with marketing leadership to pinpoint how data science can be further integrated into Asana's business approach, and provide hands-on technical mentorship and guidance to a team of data scientists.
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making
• Proven track record developing, deploying, and maintaining scalable production ML solutions and data products
• Demonstrated curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making
• 4+ years of experience collaborating with Marketing functions on deep technical projects, with extensive experience designing, implementing, and deploying marketing models (e.g. MMM, LTV, MTA, Uplift)
• Expert-level knowledge in advanced statistical modeling, causal inference, experimental design and analysis, and machine learning techniques relevant to marketing effectiveness
• 6+ years of experience in a data science role, with 2+ years dedicated to technical leadership and mentorship of other data scientists, successfully driving the architecture and execution of large-scale production data science projects
• Technical Stack: Expert proficiency in SQL and Python. Experience with MLOps tools (e.g., MLFlow), statistical languages (e.g., R), and distributed data processing systems (e.g., Spark, Redshift) is a plus
• Bachelor Degree in Math, Statistics, Computer Science, Engineering a related quantitative field, or equivalent experience