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About the Role
Own customer deployments for an early-stage SaaS company, from understanding business goals and connecting to data through delivering a trusted system with measurable impact. The role brings together data engineering, applied AI, and customer success, while also building reusable tools and practices to improve future deployments.
Responsibilities
- Partner with revenue and operations leaders to understand business objectives and identify valuable problems to solve.
- Lead customer onboarding, scope data access, and map undocumented warehouse schemas to business concepts.
- Interview customer data and business teams to reconcile conflicting definitions and validate the resulting ontology.
- Build customer-facing signals and workflows, including custom agent configurations, and troubleshoot their outputs.
- Agree on success measures, analyze results, and build a credible evidence-based case for customer impact.
- Develop reusable validation frameworks, evaluation harnesses, and mapping tools to accelerate deployments.
Requirements
- At least 3 years of experience in a technical, customer-facing role such as forward deployed engineering, solutions engineering, or software engineering with substantial customer exposure.
- Strong SQL and dbt skills, with deep familiarity navigating data warehouses and undocumented schemas.
- A quantitative degree in statistics, mathematics, computer science, or a comparable field, plus a foundation in data science or machine learning.
- Applied statistics and modeling experience, including distributions, seasonality, validation design, and calibration.
- Experience creating custom agent setups beyond default implementations and building analytical cases tied to customer outcomes.
- Ability to resolve inconsistent business definitions through interviews and data validation, with careful attention to detail and comfort working through ambiguity.
- Founder experience or a non-traditional path into engineering is a plus.
Skills
- SQL
- dbt
- Data Warehousing
- Data Science
- Machine Learning
- Applied Statistics
- Modeling
Location
- New York City, United States
Work Type
- On-site
- Full-time
Experience Level
- 3+ years
Education Level
- Quantitative degree in statistics, mathematics, computer science, or a comparable field
Salary/Compensations
- $180,000 to $250,000 USD annually