Job Summary
This hybrid data engineering and data architecture role focuses on designing and operating scalable data platforms that power machine learning solutions for hotel domain use cases. The candidate will build and optimize pipelines orchestrate ML Ops workflows on Google Vertex AI and ensure high quality data for predictive models that drive hotel revenue guest experience and operational efficiency across an international enterprise.
Responsibilities
- Design robust data architectures that unify hotel operational reservation loyalty and pricing data into scalable models that support advanced analytics and machine learning across the enterprise.
- Develop efficient data pipelines that ingest transform and validate hotel domain data to create reliable feature stores optimized for training and serving models in Google Vertex AI environments.
- Implement ML Ops practices that automate model training validation deployment and monitoring so that hotel related machine learning solutions remain accurate reliable and compliant with enterprise standards.
- Configure and manage Vertex AI workflows that orchestrate end to end machine learning lifecycles including data preparation experimentation hyperparameter tuning and model promotion to production for hotel use cases.
- Optimize data storage strategies for structured and unstructured hotel data so that analytical queries and real time scoring workloads achieve consistent performance and cost efficiency in hybrid cloud settings.
- Collaborate with data scientists to translate hotel specific analytical requirements into production ready data assets and deployment patterns that enable rapid experimentation and safe rollout of new models.
- Establish rigorous data quality rules and monitoring that continuously evaluate hotel data feeds such as bookings inventory rates and guest profiles to reduce downstream model drift and operational incidents.
- Create reusable patterns and templates for ML Ops including versioning logging alerting and rollback mechanisms that simplify ongoing support of hotel focused machine learning services.
- Document data models pipelines and ML Ops processes in accessible formats so that product operations and analytics teams can understand dependencies and safely evolve hotel domain solutions over time.
- Partner with hotel business stakeholders to identify high impact data and machine learning opportunities that improve occupancy optimize pricing reduce cancellations and enhance guest satisfaction metrics.
- Ensure compliance with data governance and privacy guidelines when handling guest and transaction records so that hotel machine learning applications maintain trust and meet regulatory expectations.
- Support hybrid work collaboration by using shared tools clear communication practices and scheduled touchpoints that keep distributed teams aligned on hotel data platform priorities and delivery timelines.
- Monitor production workloads during day shifts and coordinate planned maintenance windows so that hotel systems experience minimal disruption while data and model improvements are introduced.
Qualifications
- Combine practical experience in Google Vertex AI with strong understanding of ML Ops concepts to design maintainable workflows that scale across multiple hotel related machine learning projects.
- Apply solid knowledge of machine learning fundamentals including feature engineering evaluation metrics and model lifecycle management to deliver dependable solutions in hotel business contexts.
- Demonstrate hands on data engineering proficiency with batch and near real time processing so that hotel transaction streams and operational feeds are consistently available for analytics and models.
- Bring proven background working within hotel or hospitality domain environments where data is used to drive revenue management guest personalization or operational optimization outcomes.
- Utilize strong analytical and problem solving abilities to diagnose data pipeline issues assess model performance in hotel scenarios and implement targeted improvements that enhance business value.
- Leverage clear communication and stakeholder engagement skills to explain complex data and machine learning concepts in simple terms that support decision making across hotel operations and technology teams.
Salary and Other Compensation:
The annual salary for this position is between $75-85K depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
· Medical/Dental/Vision/Life Insurance
· Paid holidays plus Paid Time Off
· 401(k) plan and contributions
· Long-term/Short-term Disability
· Paid Parental Leave
· Employee Stock Purchase Plan
Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable la
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。
