Build and deploy data models and algorithms that improve tax accuracy, anomaly detection, and operational efficiency.
Develop risk, quality, and confidence scoring across filings, transactions, and customer data.
Partner closely with Operations, Product and Engineering, to productionize models and integrate them into core workflows.
Design experiments and analyses to inform product decisions, automation strategies, and prioritization.
Identify patterns in large, messy, multi-source datasets (e.g., payments, e-commerce, filings, customer behavior).
Improve data reliability and observability across pipelines used by analytics, ops, and ML systems.
Collaborate with Data Analysts and Ops teams to translate operational pain points into scalable, data-driven solutions.
Help define Numeral’s long-term data science and ML roadmap.

Requirements

5+ years of experience in Data Science, Applied ML, or advanced Analytics.
Strong proficiency in Python and SQL.
Experience building and shipping models or data products used in production.
Solid grounding in statistics, experimentation, and data modeling.
Ability to reason through ambiguity and design solutions from first principles.
Strong communication skills - able to explain complex ideas clearly to technical and non-technical partners.
Comfort working in a fast-paced startup environment with real ownership and minimal process.

Benefits

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonSQLdata modelingstatisticsmachine learningdata analysisalgorithm developmentanomaly detectiondata reliabilitydata pipelines

Soft Skills

communicationproblem-solvingcollaborationadaptabilitycritical thinkingcreativityownershipambiguity managementanalytical thinkingprioritization