About the job
About the Role
Join our dynamic Marketing Innovation team as a Data Scientist, where you will play a pivotal role in developing innovative internal tools and systems that revolutionize our marketing strategies and enhance customer engagement.
Our mission is to create product-like systems that:
Provide personalized, consultative experiences to millions of SMB customers through intelligent lifecycle and sales interactions.
Tailor messaging, creative solutions, and outreach based on real-time behavioral insights.
Facilitate intelligent routing, targeting, and engagement at scale, minimizing the need for manual intervention.
In this position, you will collaborate closely with Product and Engineering teams to ensure that our systems deliver measurable business value.
What You’ll Do
Establish success metrics for marketing systems (e.g., incremental pipeline generated, conversion improvements, efficiency gains), incorporating leading indicators for ongoing refinement.
Create measurement and experimentation frameworks for continuous systems across lifecycle automation, creative generation, targeting, and routing, employing methods like holdouts, staged rollouts, and quasi-experimental designs.
Collaborate with Product Managers and engineers to track, assess, and analyze system launches, ensuring every significant release is observable and accurately evaluated for incremental impact.
Convert behavioral and model-driven insights into strategic decisions: determining what to scale, identifying intervention points, and optimizing resource allocation across segments.
Develop repeatable decision-making processes (pre-launch criteria → post-launch evaluation → subsequent actions) that translate analysis into tangible improvements.
What We’re Looking For
A minimum of 10 years of experience in a quantitative role (e.g., Data Science, Decision Science), ideally within a product-focused organization fostering B2B growth, with familiarity in SMB or scaled self-service models.
Strong foundation in experimentation, causal inference, and applied statistics, with a track record of designing and interpreting tests in real-world, always-on environments.
Proficient in SQL and Python, with the ability to work with complex, incomplete behavioral datasets to assess impact.
Demonstrated success in translating findings into impactful decisions (product development, lifecycle management, targeting, routing).
Excellent communication skills to convey complex data insights to diverse audiences and stakeholders.

