Machine Learning Scientist+Agentic
Job Summary
Architect role in a global organization focused on designing scalable data solutions using BigQuery ML Python and BigQuery. The architect will define modern analytics architecture enable advanced machine learning capabilities on cloud data platforms and guide teams to deliver secure high performance solutions that drive business value and social impact within a hybrid work model.
Responsibilities
- Design end to end cloud data architectures that leverage BigQuery and BigQuery ML to deliver scalable analytics platforms that support complex business reporting and predictive modeling needs for diverse stakeholder groups.
- Develop robust machine learning solutions in BigQuery ML using Python based feature engineering and model evaluation practices that improve decision quality across critical business processes and external customer services.
- Optimize data warehouse structures and BigQuery query performance by defining partitioning strategies clustering approaches and cost control mechanisms that ensure efficient use of resources and rapid insight generation.
- Collaborate with product owners data scientists and engineering teams to translate analytical requirements into technical blueprints that integrate BigQuery data assets Python workflows and downstream consumption layers.
- Establish standards for data ingestion transformation and storage in BigQuery including reusable patterns for Python based pipelines to ensure reliability auditability and consistent data quality across projects.
- Create architecture documentation and solution diagrams that clearly describe data flows security controls and integration touchpoints enabling teams to implement BigQuery and Python solutions with confidence and alignment.
- Guide teams on best practices for experimenting with BigQuery ML models including model selection training validation and monitoring to ensure models remain accurate ethical and relevant to business objectives.
- Coordinate hybrid work collaboration by defining processes and tools that support effective communication code review and design validation for team members working both onsite and remotely in day shift.
- Ensure security and compliance requirements are embedded into all BigQuery and Python solutions by applying encryption access control policies and data governance principles that protect sensitive information and build stakeholder trust.
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
申请人可能需要通过现场面试或视频会议的方式参加面试。此外，候选人在每次面试时可能需要出示其当前所在州或政府签发的有效身份证件。
Cognizant 是一家提供平等就业机会的雇主。在招聘过程中，您的申请和候选资格不会因种族、肤色、性别、宗教、信仰、性取向、性别认同、国籍、残疾、遗传信息、怀孕、退伍军人身份或任何其他受联邦、州或地方法律保护的特征而受到影响。
