About this role
Analytical professionals who thrive in ambiguity and enjoy building functions from scratch will find a natural home in this role. Boulevard is establishing a dedicated Product Intelligence function for its client experience platform, and this practitioner will own the foundation from day one. Daily work spans engineering the underlying data stack, partnering with product teams on feature experimentation, and developing predictive machine learning models that decode how salon and spa operators use the software.
The organization has scaled past 5,000 business customers processing billions in annual payments, creating a rich environment for data exploration. Rather than maintaining existing systems, the person taking on this challenge will define tracking standards, build self-serve analytics dashboards, and translate complex behavioral metrics into strategic decisions for leadership. Success requires a rare blend of data engineering capability, statistical rigor, and clear storytelling to shape the product roadmap.
What you will do
- Partner across the Product Development organization to define event schemas and build reliable, analysis-ready data assets in collaboration with data engineering.
- Develop data-driven recommendations that inform strategy through engaging narratives and visualizations adapted for audiences ranging from individual contributors to executive leadership.
- Build scalable, self-serve dashboards using platforms like Sigma, Looker, or Tableau to empower stakeholders to independently explore data.
- Conduct deep-dive exploratory analyses including funnel diagnostics, retention curves, and feature adoption studies to influence product direction.
- Own the experimentation practice for Product Development by designing hypothesis-driven tests, determining power and duration, and delivering defensible reads on feature impact.
- Apply statistical and machine learning methods such as regression, classification, and churn-risk modeling to explain and predict customer behavior.
- Move models into production by partnering with data engineering to schedule, monitor, and version pipelines that feed action into operational workflows.
What you need
- Bring 8+ years of proven experience in data science, product analytics, or engineering within a B2B SaaS or high-growth technology environment.
- Demonstrate hands-on experience in early-stage or low data-maturity settings where you built foundational analytics infrastructure rather than maintaining existing systems.
- Possess fluency with SQL, Python, Snowflake, dbt, Sigma, and AWS infrastructure used for data and reporting pipelines.
- Show direct experience designing and executing product instrumentation strategies, defining event schemas, and authoring tracking plans.
- Exhibit significant experience working directly with product managers to translate statistical findings into decision-ready narratives and roadmap investments.
- Apply deep statistical and machine learning expertise to customer behavior including propensity modeling, segmentation, and survival analysis with rigorous validation.
Skills and tech stack
Questions candidates ask
What is the work location policy for this role?
The position is listed as Remote - USA.
What is the salary range for this position?
The salary range for this role is $164,000 - $205,000.
What tools and technologies will I be using?
The tech stack includes SQL, Python, Snowflake, dbt, Sigma, AWS, and BI tools like Looker or Tableau, alongside Statsig for experimentation.
What kind of environment will I be working in?
This role requires someone genuinely energized by ambiguity who can define questions, build infrastructure, and chart the course forward without a well-worn path to follow.