Staff Data Scientist

We're seeking a Staff Data Scientist to support the continued evolution of a document verification and fraud prevention platform used across highly scaled digital environments. This role blends applied machine learning, experimentation, analytics, and product-focused problem solving. You'll work closely with engineering, product, and operations teams to develop models, uncover insights, and build frameworks that improve both performance and decision-making.

Key Responsibilities

• Develop and enhance machine learning solutions focused on identity verification, document analysis, fraud detection, image assessment, and biometric-related use cases.


• Explore new data signals, modeling techniques, and detection strategies to improve prediction accuracy and risk outcomes.


• Collaborate with engineering teams to launch, monitor, and refine models operating in live environments.


• Investigate fraud patterns, customer behaviors, and emerging threats using large-scale datasets.


• Design rigorous model assessments and performance studies using offline and production data.


• Establish metrics, reporting frameworks, and monitoring capabilities to track model effectiveness and business impact.


• Create internal tools that streamline evaluation workflows, investigations, experimentation, and operational processes.


• Partner with stakeholders across product, operations, and technology teams to translate business challenges into data-driven solutions.


• Present findings and recommendations that help guide product strategy and machine learning investments.

Requirements

• Advanced degree or equivalent industry experience in Data Science, Computer Science, Statistics, Mathematics, or a related technical discipline.


• 5+ years of experience working in machine learning, advanced analytics, fraud, risk, or data science environments.


• Demonstrated success building, validating, and improving machine learning models used in production.


• Strong proficiency with Python and SQL.


• Experience leveraging modern data and ML platforms such as Databricks, Spark, SageMaker, or similar ecosystems.


• Solid foundation in experimentation, statistical methods, model measurement, and performance analysis.


• Ability to communicate complex analytical findings to both technical and non-technical audiences.

Compensation: Competitive base salary, equity opportunity, and comprehensive benefits package.