Arch
Data Scientist
San Francisco · Exec
Sponsorship not specifiedDetected 399 days ago
PythonFull-Stack DevelopmentSQLMachine LearningPyTorchscikit-learnAirflowdbtData EngineeringData ScienceMarketing AnalyticsLeadership
About the role
- The US $800 billion frontline-services sector underpins the nation, yet many of these critical businesses still rely on spreadsheets, outdated software, and paper forms.
- We're driving energy resilience, economic strength, and long-term prosperity by bringing AI innovation to the services that need it most-starting with home energy.
Responsibilities
- Analyze product performance and customer usage to inform roadmap and product design
- Collaborate with the engineering team to productionize ML pipelines and integrate them into our backend systems
- Work closely with leadership to build internal analytics, dashboards, and investor-facing insights
- Develop and deploy predictive models to identify high-conversion leads and drive campaign targeting
- Own the full ML lifecycle: from data acquisition, cleaning, and labeling to modeling, validation, and deployment
Requirements
- 3-6 years experience in data science, ML engineering, or analytics roles in fast-paced environments
- Proficiency in Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, or PyTorch)
- Familiarity with data pipelines, model evaluation, and deployment workflows
- Proven ability to work independently in ambiguous contexts with high judgment and ownership
- Experience working with business stakeholders to translate messy data into actionable insights
- Experience with large-scale structured data (e.g., property, utility, or energy-related datasets)
- Knowledge of marketing analytics, targeting models, or customer segmentation
- Familiarity with modern data tooling (e.g., dbt, Airflow, Dagster, DuckDB)
- Comfort with basic full-stack workflows or collaborating in a product engineering environment
Compensation
- Competitive salary + significant equity package based on experience.
Benefits
- You'll work directly with our CTO and founding team to model customer behavior, optimize campaign performance, and build scalable, production-ready machine learning systems.
This listing is sourced directly from Arch's careers page and normalized into a canonical job model.