Staff / Principal Data Scientist (US)

About the role

Auror's North American footprint is live and expanding. We need a highly practical and rigorous Data Scientist to build, productionize, and defend predictive models that customers can trust, especially for high-stakes operational decisions in Loss Prevention and Fraud detection (e.g., cashier risk scoring, deployment optimization, shrink prediction). This role fills a current need for deep statistical modeling expertise combined with real-world domain knowledge and the ability to ship robust analytics products.

Responsibilities

• Own predictive modeling and advanced analytics end-to-end, from ambiguous problem framing to deployment, focusing on Loss Prevention (LP) and Asset Protection (AP) applications.
• Design, build, and standardize ETL pipelines and data architecture necessary to support robust, scalable predictive modeling at scale.
• Build defensible metrics (calibration, error tradeoffs, bias/disparity checks) and link them to measurable decision outcomes for C-suite and AP teams.
• Partner with ML engineers to productionize: feature definitions, scoring workflows, monitoring signals, and retraining triggers.
• Communicate clearly and concisely to diverse audiences (internal Product/Engineering, external customers, and executive teams) on model uncertainty, value, and strategic application.
• Design randomized controlled trials and evaluation harnesses that make model quality legible to stakeholders and customers.

Requirements

• Expertise in practical statistical modeling and analysis (inference, causal/experimental thinking, time series, model calibration, measurement) applied to real-world, messy data.
• Demonstrated experience taking analyses/models from ambiguous problem → shipped decision support (e.g., shortage prediction, risk classification models).
• Strong domain expertise in Retail Loss Prevention, Fraud detection, Asset Protection, or POS Analytics.
• Strong SQL + Python, with demonstrated experience in ETL Pipeline Design and Data Modeling & Architecture.
• Practical, high-integrity approach to responsible AI (limits, misuse risk, bias considerations, auditability).
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• Experience with geospatial risk modeling, network/graph analytics, or Exception Based Reporting (EBR) tools.
• Experience building customer-facing proofs-of-concept and translating complex analytics into product features.

Benefits

Additional Information

About Auror At Auror, we're empowering the retail industry to tackle theft and Organised Retail Crime, a $150 Billion problem globally. It's high volume crime that's increasingly organised in nature and is putting people, retailers, and communities at risk every day. Founded in New Zealand 12 years ago, we're working with some of the best and largest retailers in the world across the US, Canada, Australia, New Zealand, and the UK. Auror is connecting people and intelligence to reduce crime. We're using technology for good. Our mission is clear: reduce violent retail crime by 50% in 5 years. It's an ambitious goal - and one we believe is achievable. In partnership with our leading retail partners, we need people with the passion, determination, and innovation required to overcome one of the world's largest problems. If you're looking to make a difference with and for the people dedicated to stopping crime, for good, then we want you on our team. We're also embracing the potential of AI to supercharge our impact - whether that's enhancing the way we detect trends, support our customers, or improve internal workflows. As a company, we're committed to responsibly incorporating AI into how we work and what we build, and we encourage all Aurors to be curious about how AI can elevate their work, regardless of role or function.

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