10 часов назад
Data Science Product Owner
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Science Product Owner (Machine Learning/Data Analytics): Leading the strategy, prioritization, and delivery of enterprise data science products and capabilities with an accent on backlog management, requirements definition, and cross-functional agile delivery. Focus on translating business needs into machine learning and analytics requirements, validating model outputs, monitoring KPIs, and maintaining governance traceability.
Location: Plano, Texas, United States. Must already have the right to work in the United States; visa or employment-based immigration sponsorship is not available now or in the future.
Company
Financial Services is and Lexus's North American finance and insurance business, delivering customer-focused financial services and data-driven solutions.
What you will do
- Own and maintain the backlog for data science products, use cases, and enhancements.
- Translate business goals into user stories, requirements, acceptance criteria, and delivery priorities.
- Gather requirements for machine learning models, analytics, predictive capabilities, and automated decisioning.
- Partner with business leaders, product managers, data scientists, engineers, QA, and technical teams to align scope and priorities.
- Support agile ceremonies, release readiness, dependency coordination, and risk escalation.
- Define validation criteria and monitor model performance, experimentation results, adoption, KPIs, and business impact.
Requirements
- Bachelor's degree in a relevant business, technical, data science, statistics, mathematics, economics, or related field, or equivalent experience.
- 4+ years of experience in product ownership, business analysis, analytics, or delivery coordination in a technical or data-driven environment.
- Knowledge of Agile frameworks and product backlog management.
- Experience with Jira, GitHub, Confluence, and similar collaboration tools.
- Understanding of data science concepts including model development, experimentation, deployment, and monitoring.
- Experience with SQL, Python, reporting, dashboards, or analytics tools, with the ability to write credible requirements without building models directly.
Nice to have
- Experience with A/B testing, experimental design, machine learning lifecycle, or MLE practices.
- Experience with data pipelines, dashboards, or data quality processes.
- Financial services or banking experience.
- Experience with cloud environments such as AWS.
Culture & Benefits
- Team-oriented, flexible, and respectful work environment.
- Professional growth programs and tuition reimbursement.
- Health care, wellness plans, paid holidays, and paid time off.
- 401(k) plan with company match and possible annual retirement contribution.
- Vehicle purchase discount and lease vehicle program, where applicable.
- Relocation assistance and tax-advantaged accounts, where applicable.
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