Shape the future of sales intelligence by building robust, self-correcting data systems that power strategic decision-making at scale. This role sits at the intersection of advanced analytics, automation, and executive communication, driving how sales targets, incentives, and capacity are modeled and managed.
What You’ll Do
- Develop and maintain automated pipelines for quota and incentive planning, with built-in validation and error prevention to ensure data reliability
- Leverage large language models and prompt engineering to streamline code development, auditing, and system documentation
- Extract, validate, and enrich high-volume datasets from Snowflake and GitHub, ensuring consistency across layered logic and transformations
- Translate statistical outputs into clear, actionable strategies for senior leaders, using data storytelling to influence direction
- Apply predictive techniques—including regression, clustering, and simulation—to assess sales coverage and improve customer engagement strategies
What We’re Looking For
- Expertise in Python, particularly Pandas and Google Cloud libraries, for scalable data processing
- Strong command of SQL, with experience in Snowflake and DBeaver for querying and optimizing large datasets
- Proven background in statistical methods: regression, decision trees, scenario modeling, and pattern analysis
- Experience with GitHub for version-controlled, collaborative development
- Ability to create resilient, self-healing scripts that proactively resolve data issues
- Track record of delivering insights through Tableau, Google Sheets, and Salesforce CRMA with clarity and impact
- Minimum of 10 years working with large-scale data and production-level statistical systems
- Bachelor’s degree in Statistics, Mathematics, Computer Science, or a related quantitative discipline
Nice-to-Have
- Background in Sales Operations, Finance, or Go-To-Market strategy in technology organizations
- Comfort operating in ambiguous, fast-moving environments where frameworks are still evolving
- Experience treating AI as a core partner in development, using prompt engineering to accelerate delivery
- A builder’s mindset—focused on automating processes and eliminating root causes of errors
Technology Environment
Python, Pandas, Google Cloud Platform, SQL, Snowflake, DBeaver, GitHub, Tableau, Google Sheets, Salesforce CRMA, LLMs, and prompt engineering workflows.
Work Environment
This is a hybrid role based in the United States, with flexibility in work setting—options include in-office, office-flex, or remote. Compensation may vary by location for remote roles.
Our Culture
We value open collaboration, diverse perspectives, and challenging conventional thinking. Innovation thrives here through inclusion, transparency, and contributions from people of all backgrounds. We champion ideas based on merit, not hierarchy, and are committed to equitable practices across all stages of employment.
