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
コグニザントについて
コグニザント（NASDAQ: CTSH）は、AI Builderおよびテクノロジーサービスプロバイダーとして、お客様にフルスタックのAIソリューションを構築することで、AI投資と企業価値を結ぶ架け橋となっています。業界、ビジネスプロセス、エンジニアリングに関する当社の深い専門知識を活かし、組織固有のビジネス環境をテクノロジー・システムに組み込みます。これにより、人間の可能性を最大限に引き出し、確かな成果を実現するとともに、急速に変化する世界においてグローバル企業が常に一歩先を行くための支援を行っています。 詳細については、cognizant.ai をご覧ください。
雇用に関する追加情報
本募集に記載されている報酬情報は、掲載日時点で正確なものです。Cognizantは、適用される法令に従い、いつでも本情報を変更する権利を留保します。
応募者は、対面またはビデオ会議による面接への参加を求められる場合があります。また、各面接の際に、現在有効な州政府または政府発行の身分証明書の提示を求められる場合があります。
Cognizantは機会均等雇用主です。応募および選考において、人種、肌の色、性別、宗教、信条、性的指向、性自認、国籍、障がい、遺伝情報、妊娠、退役軍人の地位、その他連邦法・州法・地方自治体の法律により保護されるいかなる特性に基づく差別も行いません。
