What are the responsibilities and job description for the Data Scientist, Modeling & Analytics position at Carpe?
To Apply
To apply directly to this role, please email daniel@mycarpe.com your non-LLM paragraph explaining why you believe you would be the best fit for this role with a pdf of your resume attached. Applying via email is the only way to be considered.
About Carpe
Carpe is the fastest-growing deodorant brand in the US. Our team is composed of ~30 insanely smart people working together in person in downtown Durham, NC. Our office is rather open with many private niches, and our energy level is HIGH.
About the Role
We are looking for a Full-Stack Data Scientist who sits at the intersection of data science and the business, and who pairs a strong model development background with the judgment to turn business questions into actionable predictions, models, and recommendations. You will own the full path from raw data to insight: engineering reliable data pipelines, building and validating models, and translating the results into opportunities the business can act on.
You will help strengthen our data stack using Looker, LookML, SQL, Snowflake, and dbt, and you will bring exceptional rigor — checking your own work, writing unit tests against your data and models, and catching problems before they reach stakeholders. Your day-to-day direction will come from the VP of Ecommerce. The right candidate understands both the math and the story behind it and can build models and tools that let the business make smarter, faster decisions.
What You’ll Do
• Translate business questions and objectives into well-scoped analyses, predictive models, and clear recommendations that surface opportunities and drive decisions.
• Build, train, validate, and maintain data systems with a strong focus on accuracy and reproducibility.
• Ensure accurate, well structured data integration into our AI systems by validating inputs, mappings, and outputs so models and AI-driven tools run on trustworthy, clean data.
• Engineer and maintain reliable data pipelines that feed models and reporting; contribute to and strengthen our data stack.
• Build and improve models and metrics in Looker so the business can self-serve trustworthy data.
• Write unit tests and data-quality checks against pipelines and model inputs/outputs; sanity-check your own work and escalate anomalies before they reach stakeholders.
• Interrogate results with a critical eye — understand what a model is actually telling you, quantify uncertainty, and avoid misleading conclusions.
• Collaborate cross-functionally (ecommerce, finance, retail, marketing, operations) to make sure models and data reflect real business activity.
• Document methodology, model logic, and data definitions to maintain institutional knowledge and consistency.
• Monitor deployed models and metrics over time; retrain, refine, and improve as the business evolves.
What We’re Looking For
• 3–7 years building data science models in a production or business-facing setting.
• Strong model development background. You can design, build, and validate models, not just run notebooks or read outputs.
• Hands-on data pipeline engineering: comfortable owning data from source to model.
• Ability to turn ambiguous business questions into structured, testable analyses and clear recommendations.
• Exceptional attention to detail. You actively look for errors, write unit tests, and check your work before others do.
• Strong analytical judgment: you understand what a model is saying, its assumptions, and its limits.
• Comfortable working with large, messy datasets and translating them into clear narratives.
• Strong communication skills; able to explain models and findings clearly to both technical and non-technical stakeholders.
• Knowledge of DTC, ecommerce, or CPG businesses is helpful but not required.
• Experience with Daasity is helpful but not required.
Preferred Background
Experience building models within a growth-stage ecommerce, DTC, or CPG business is a strong plus. Candidates who have worked with performance marketing and customer data (Meta, Google, subscription/retention data) and understand how those signals feed into forecasts and financial models will stand out. Prior work modernizing a data stack with dbt, LookML, and rigorous testing is highly valued.
Why This Role
This is a high-visibility position with direct access to senior leadership. You will play a central role in how the company understands and predicts its performance — and you will have the autonomy to build the models, pipelines, and processes that make that possible.
To Apply
To apply directly to this role, please email daniel@mycarpe.com your non-LLM paragraph explaining why you believe you would be the best fit for this role with a pdf of your resume attached. Applying via email is the only way to be considered.