Senior Data Scientist

About Sundays for Dogs

Sundays for Dogs is a founder-led, direct-to-consumer brand reimagining pet food so dog owners can spend more quality time with their dogs — now and later. We make human-grade, air-dried food that supports long, healthy lives, and we build our company around shared core values that guide how we work and how we treat each other.

We’re headquartered in Cleveland, Ohio, with a primarily remote team of ~50 full-time employees across the U.S. While we work distributed day to day, we come together in person on a quarterly basis because relationships matter. Our business today is 100% DTC, with our subscription model at the core of how we serve customers — and we’re building to scale with intention. We’re just getting started...

## About your team and position:

We’re hiring a Senior Data Scientist to help define how Sundays uses data to scale the business. This is a high-impact role on a small, scrappy, and fast-moving team that is in the early stages of building best-in-class data infrastructure and modeling capabilities from the ground up.

Reporting to our newly appointed VP of Data, this role blends data science, analytics, and platform-building. You’ll partner closely with our newly established Analytics Engineering function to help shape our analytics foundation — from scalable data models and modern BI tooling to the first generation of production-grade data science models.

While there is tremendous opportunity to apply advanced data science techniques, this role will also spend meaningful time on core analytics, especially early on. As a new team, we’re simultaneously building the foundation and delivering insights, so you’ll need to be comfortable flexing between deep modeling work and hands-on analytical problem-solving.

You’ll have significant ownership in shaping how data is used at Sundays — identifying the highest-impact opportunities for data science, building models and analytical frameworks, and helping the company act on what we learn.

This role is fully remote within the U.S., with travel to our Cleveland headquarters for onboarding and quarterly in-person collaboration.

Your day-to-day

• Partner with stakeholders across Marketing, Product, Finance, and Operations to frame business problems and identify where data science and analytics can drive the most impact.
• Develop and deploy data science models (e.g., LTV prediction, churn/retention modeling, propensity scoring, forecasting) to inform growth and operational decisions.
• Perform high-impact exploratory and ad-hoc analyses to answer critical business questions and move quickly on strategic decisions.
• Work closely with Analytics Engineering to translate business needs into scalable datasets, feature sets, and production-ready models.
• Help define and standardize key business metrics, ensuring alignment between analytical outputs and modeled insights.
• Contribute to the rollout and adoption of our dbt project and BI tooling, ensuring models and analyses are built on reliable, well-structured data.
• Build and maintain dashboards and reporting frameworks that complement and operationalize data science insights.
• Design, analyze, and interpret experiments (A/B tests) to evaluate product, marketing, and lifecycle initiatives.
• Investigate performance changes, diagnose root causes, and communicate clear, actionable recommendations to stakeholders.
• Help establish best practices for data science and analytics as we scale the function.
• Work with data and engineering partners to ensure analytical work is built on scalable, reliable data models.

We'd love to hear from you if you have

• 6+ years of experience in data science, analytics, or related quantitative roles.
• Strong SQL skills and deep experience working with modern cloud data warehouses (e.g., Snowflake, BigQuery, Databricks) and transformation tools like dbt.
• Strong experience in Python (or similar) for data analysis, statistical modeling, and/or machine learning.
• Experience building and applying models such as LTV prediction, churn/retention models, forecasting, Media Mix, Multi-touch Attribution or propensity models in a business context.
• A strong understanding of DTC and ecommerce metrics, including CAC, LTV, cohort analysis, retention, and forecasting.
• Experience designing and analyzing experiments (A/B testing).
• A track record of using data (both analytics and modeling) to influence strategy and drive measurable business outcomes.
• Comfort operating in a scrappy, fast-moving environment where you balance foundational work, analytics, and modeling simultaneously.
• Experience partnering directly with cross-functional stakeholders and senior leaders to translate insights into action.
• Strong communication skills and the ability to clearly explain both analytical findings and model outputs to technical and non-technical audiences.
• Strong judgment in identifying when to apply advanced data science vs. simpler analytical approaches.