Senior Applied Scientist, Trust & Safety

Senior Applied Scientist – Trust & Safety Science DAT’s Trust and Safety Science team is seeking a Senior Applied Scientist to design and deploy the next generation of risk models and intelligent decision systems that detect, prevent, and mitigate unsafe, fraudulent, or otherwise harmful behavior across our network. This role sits at the intersection of machine learning, risk decisioning, and product development, focusing on building systems that protect customers and the marketplace while preserving healthy marketplace activity. Responsibilities Conceptualize, propose, implement, and iterate on models and algorithms for fraud detection, risk scoring, and trust and safety decisioning. Build decision engines that learn from feedback and support actions such as step‑up verification, review prioritization, and automated access controls. Apply machine learning, graph and network algorithms, anomaly detection, and other quantitative methods to deliver measurable improvements in fraud prevention and operational effectiveness. Take ideas from research to production, ensuring the solutions you build integrate cleanly into operational and product systems. Build and productionize fraud, safety, and risk systems for high‑recall decisioning, with controls that preserve precision, fairness, and explainability in high‑stakes workflows. Design graph, network‑link analysis, entity‑resolution, and anomaly‑detection algorithms that identify hidden relationships, behavioral drift, account abuse, and emerging threat patterns across users, carriers, digital fingerprints and physical assets. Develop continuous risk monitoring, alerting, and policy decisioning across onboarding, booking, and load execution, combining ML models, heuristics, feedback loops, and human‑in‑the‑loop review where appropriate. Move proactively and with urgency against evolving fraud patterns, rapidly iterating on approaches while building scalable, adaptable detection and decisioning systems rather than brittle one‑off patches or manual hacks. Qualifications PhD or MS in Computer Science, Statistics, Applied Mathematics, Operations Research, Engineering, or another quantitative field. 5+ years of experience developing and deploying machine learning, statistical, or decisioning solutions in production environments, with strong proficiency in Python and modern ML tooling and hands‑on experience building reliable, production‑quality data and model workflows. Ability to develop algorithmic solutions and decision systems while maintaining explainability, interpretability, and defensibility in high‑stakes risk and compliance workflows. Experience owning a model, service, API, or pipeline end‑to‑end, including quality, monitoring, iteration, and cross‑functional coordination, with strong communication and collaboration skills to work effectively with technical and non‑technical partners and bring models into production. Demonstrated ability to frame ambiguous business problems as scalable automated decision systems and deliver practical solutions with measurable impact. Experience in one or more of the following areas: fraud detection, trust and safety, risk modeling, anomaly detection, rare‑event modeling, identity or abuse detection, graph or network analysis, or related decision systems. Bonus Skills You have worked on systems that combine models, heuristics, human review, and operational workflows to make high‑stakes decisions. You have experience with two‑sided marketplaces, pricing, financial markets, or economic systems. You have experience in freight, logistics, transportation technology, or adjacent operational domains. Benefits Medical, Dental, Vision, Life, and AD&D insurance Parental Leave Flexible Vacation Time (FVT) An additional 10 holidays of paid time off per calendar year 401(k) matching (immediately vested) Employee Stock Purchase Plan Short‑ and Long‑term disability sick leave Flexible Spending Accounts Health Savings Accounts Employee Assistance Program Additional programs – Employee Referral, Internal Recognition, and Wellness Free TriMet transit pass (Beaverton Office) Competitive salary and benefits package Work on impactful projects in a cutting‑edge environment Collaborative and supportive team culture Opportunity to make a real difference in the trucking industry Employee Resource Groups Pay Range (Washington State) For Washington‑based candidates, the salary range for this role is $183,000.00 – $226,000.00 plus target bonus. The range reflects the scope and responsibilities of the position, candidate experience and education, core skills, internal equity, and market and business factors. Equal Opportunity Employer / Protections DAT embraces the value of a diverse workforce and provides equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state, and local laws. Protected Disclosures The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information. 41 CFR 60‑1.35(c). #J-18808-Ljbffr DAT Freight & Analytics