Data Science Jobs in Richardson, TX

Leads endpoint detection engineering using AI, machine learning, Detection-as-Code, behavioral analytics, and MITRE ATT&CK. Owns detection coverage from telemetry onboarding through alert deployment, tuning, and gap analysis. Partners with threat intelligence, security operations, and business stakeholders to manage cyber risk and compliance. Conducts threat research, aligns detection capabilities with red-team techniques, mentors engineers, and drives architecture decisions for scalable, high-fidelity endpoint protections.

Lead data science and NLP initiatives for AI-powered products, partnering with engineers, machine learning specialists, and product managers. Build, fine-tune, evaluate, validate, and operationalize large language and machine learning models at scale. Apply advanced NLP, deep learning, and model training techniques while supporting model risk compliance. Translate technical findings into business outcomes and develop team talent.

Leads a strategic insights team analyzing product development productivity, operating models, workflows, and AI adoption. Frames hypotheses, conducts quantitative analysis and experiments, evaluates delivery and business outcomes, and translates findings into executive recommendations. Partners with Product Operations, Technology, Product, and Finance to implement actions, track adoption, and measure results. Establishes analytical standards, communicates with senior leaders, and develops a high-performing analytics team.

Lead enterprise product and experience initiatives, guiding cross-functional teams (product, data, design, ML, engineering) to define strategy, deliver customer-centric digital products, prototype and apply emerging AI/automation tools, and drive transformational outcomes across Capital One.

Supports data science and analytics teams by managing Jira requirements, backlogs, workflows, dashboards, model portfolios, and prioritization processes. Partners with technical teams, leadership, and stakeholders to communicate model status, risks, blockers, and priorities. The role also improves documentation and intake processes, facilitates prioritization decisions, and builds repeatable processes in a compliance-sensitive environment.

Supports business decision-making through data analysis, predictive modeling, statistical and machine learning techniques, and presentation of insights. Interns will work across marketing, lending, indirect lending, and warranties while gaining hands-on experience throughout the data science lifecycle. The role is an 11-week, paid, on-site internship based in Tempe, Arizona, or Dallas, Texas, with no relocation assistance.

Lead and deliver advanced analytics and machine learning solutions to support pricing, revenue optimization, and partner relationships. Collaborate with cross-functional teams to design, validate, and implement models at scale using large transaction datasets and modern big-data tooling. Translate technical insights into actionable business recommendations.

Lead multiple data engineering teams to ensure data quality, build and optimize data pipelines, ingest and curate diverse data sources, transform data for ML/analytics, productionize data science products, collaborate with IT for deployments, manage budgets/resources, and build business cases with ROI analyses.