A
Arcadia
Senior Data Scientist
Skills
SQL QueriesData MiningPythonNumPypandasMachine LearningAIGitHub
19 days ago
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Important information
Location:
United States
Work mode:
Remote
Published on:
9 October 2026
What they need
Who you are
- Substantial hands-on experience building and evaluating production ML models, with the judgment to make progress on ambiguous problems independently. The right person will need at least 3 years of experience working in ML models
- Strong ML fundamentals — statistics, classification, regression, and evaluation methodology
- Fluency in Python (pandas, scikit-learn, numpy) and SQL, and comfort working in a live production codebase not just notebooks
- Practical experience with LLMs or agentic workflows in production
- Comfort with imperfect ground truth and managing inherent uncertainty in data
- A track record of driving work with minimal oversight: forming and documenting assumptions, making the call on approach, and standing behind a recommendation
- Clear communication that adapts to the audience: able to explain model behavior to engineers and non-technical partners and make the case for a decision
- Bachelor's or Master's in CS, Statistics, Math, or a related field (or equivalent experience), plus a portfolio of past work — GitHub, papers, or project write-ups
What the job involves
- We're looking for a Senior Data Scientist to join Arcadia's Applied AI team — a small, delivery-focused group within R&D that ships the machine learning and AI systems powering Arcadia's utility data platform
- This is a hands-on role standing up new ML / AI capabilities across our core workstreams: utility bill data extraction, forecasting, and audit/anomaly detection
- You'll work closely with engineering partners and the Director of Applied AI, with the experience to own ambiguous problems end to end, set the technical approach where none exists yet, and help shape how the team sequences its work
- Own delivery of one or more core workstreams — bill data extraction, forecasting, or audit/anomaly detection — and flex across them with your manager as priorities shift
- Build, evaluate, and improve production models: document classifiers and extraction agents, forecasting models for bill availability and spend, and detection and tuning for audits and controls
- Set the technical approach on problems where the right method isn't established — investigate, decide, and carry the recommendation through to a shipped result
- Partner with the Director on prioritization and sequencing across workstreams, bringing a point of view on where the team should invest rather than only the capacity to execute
- Write production-grade Python and contribute to the shared codebase, pipelines, and design docs — this is a live production system, not a notebook sandbox
- Partner with engineering on model integration, monitoring, and post-deployment behavior – as the authority on the modeling approach and the team's resource for applying AI in production
- Automate manual steps in your own and the team's workflow with AI tooling, and share the techniques that raise throughput
Benefits
- Remote first culture: Work anywhere in the US as long as you have a reliable internet connection.
- Flexible PTO: No accrued hours and no limit on the number of vacation days employees can take each year.
- Medical, dental, and vision: 80-95% employer cost coverage for medical, dental, and vision benefits for employees and dependents. Transparency in coverage.
- Company-wide holidays: 15 annual company-wide holidays including a week long "summer break".
- Weekly "flex time": No internal meetings on Tuesdays and Friday afternoons.
- Paid leave: 12 weeks paid parental leave for all parents, 10 days sick leave, up to 4 weeks bereavement leave.
- Additional time off: 2 volunteer days off, 2 professional development days off.
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