Data Scientist - arch

Location: San Francisco | In-Person 3–4 Days/Week

💡 ABOUT ARCH

Arch powers frontline industries with cutting-edge AI.

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frontline-services sector underpins the nation, yet many of these critical businesses still rely on spreadsheets, outdated software, and paper forms.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.

We’re backed by Coatue, Floodgate, Gigascale, ReGen, MCJ Collective, and the founders of Aurora Solar.

Compensation

Competitive salary + significant equity package based on experience.

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ROLE OVERVIEW

We’re hiring a Data Scientist to help architect the intelligence layer of Arch. 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.

You’ll have ownership from data collection to deployment, working in a highly iterative environment with direct feedback from real-world users. Your work will power high-stakes decisions that directly impact customer outcomes, product development, and revenue.

This is a high-ownership, high-ambiguity role for someone excited to ship fast, learn from deployment, and move the needle in a mission-critical industry.

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WHAT YOU’LL DO

• 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
• 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
• Prototype, experiment, and iterate quickly—balancing rigor with speed

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QUALIFICATIONS

Must-haves:

• 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

Strong bonuses:

• 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)