Top Tech Jobs & Startup Jobs in Austin, TX

As a Senior Data Scientist, you'll develop fraud detection models, perform detailed analyses, and work closely with teams to drive product innovation and business outcomes.

Own and evolve the data infrastructure powering identity and fraud products. Build and operate scalable ETL/ELT pipelines, ensure data quality and observability, optimize storage and access, support product squads, respond to production incidents, mentor engineers, and drive data platform innovation.

As a Senior Software Engineer on the Data Platform team, you'll enhance the data infrastructure, develop ETL pipelines, maintain data quality, collaborate across teams, and mentor junior engineers.

Lead product vision and execution for internal, data-intensive technical initiatives. Improve and future-proof datasets, shared services, and platforms. Partner across engineering, data science, analytics, and product to translate needs into requirements, prioritize work, drive cross-functional delivery, define success metrics, and communicate roadmap and risks to stakeholders.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

Own full-cycle recruiting across technical, business, and go-to-market roles, from individual contributors through leadership. Partner with hiring managers and senior leaders on role definition, sourcing strategy, candidate evaluation, and hiring decisions. Manage complex searches, use funnel metrics to improve outcomes, maintain ATS rigor, enhance recruiting processes, and deliver consistent candidate experiences. Mentor recruiters and provide talent-market expertise, judgment, and stakeholder leadership.

Leads and manages an applied machine learning team developing fraud detection and identity verification models. Responsibilities include people management, coaching, code review, production ML systems, model lifecycle ownership, experimentation, deployment, monitoring, fraud research, cross-functional prioritization, and communicating results. The role remains hands-on while partnering with Product, Engineering, Risk, and leadership to drive measurable business impact and shape future product strategy using machine learning and AI.

Leads an applied machine learning team and owns fraud detection and identity model strategy, development, deployment, monitoring, and iteration. Partners with Product, Engineering, Risk, and senior leadership to set priorities and deliver business impact. Provides technical mentorship, reviews code, guides modeling and architecture decisions, researches fraud patterns, develops ML capabilities, and shapes responsible AI use under data governance and security constraints.

Lead a team of analysts and data scientists embedded in sales to build rigorous pilot analyses, create executive-ready business cases, expand consultative analytics across the partner lifecycle, and publish industry insights while coaching and scaling the Solutions Analytics function.

Manage strategic bank, credit union, and fintech accounts to drive adoption, onboarding, and product-driven fraud mitigation. Provide consultative guidance, set business goals, run trainings, share performance data, collaborate cross-functionally, support renewals, and travel to clients as needed.