Top Hybrid Data & Analytics Jobs

Focus on driving Intelsat's Information Security threat and compliance program by performing tasks related to system security, maintenance of policies, incident response, security metrics, audit engagements, and documentation. Contribute to the development and revision of security metrics and support third-party vendor security assessments. Required to have a bachelor's degree in information security or related field, fundamental knowledge of Information security, and excellent communication skills. Must be a US Person due to ITAR requirements.

Design and develop scalable and reliable solutions for data usage at Chewy. Collaborate with teams to drive innovation, solve Splunk problems, and implement integrations with external apps and systems. Responsible for data interpretation, enrichment, and managing knowledge objects in Splunk. Telecommuting permitted.

As a Data Analyst Sr within PNC's Enterprise Data Management organization, you will manage and develop information systems for clients, conduct data information analysis, advise end-users on data manipulation, and support technologies for managing and utilizing multiple information sources.

Lead in developing, supporting, and implementing data solutions for multiple applications in order to meet business objectives and user requirements. Collaborate with Capital Markets product owners to maximize revenue, minimize operational costs, and increase regulatory compliance. Expertise in building Capital Markets Data Lake, data pipelines, and automating manual processes through data automation. Financial Industry background preferred.

Designs and optimizes data warehouses, performs data analysis, develops data warehouse architecture, provides technical guidance, and ensures data quality and integrity.

The Senior Reinsurance Analyst at CNA is responsible for implementing technology-driven solutions, supporting contract administration, creating P&L statements, pursuing recovery of balances, coordinating with business units, and participating in special projects. The role offers ample growth opportunities both personally and professionally.

Looking for experienced leaders to be part of a world-class consulting organization focused on driving innovation in cloud solutions. Responsibilities include building relationships with stakeholders, leading a consulting team, developing and implementing enterprise data strategy, and influencing at a large scale.

The Corporate Development Principal Analyst will help execute financial and strategic analysis of specific potential merger & acquisition transactions. Responsibilities include creating financial models, conducting research, collaborating with cross-functional teams, and developing presentation materials. The ideal candidate should have financial modeling skills, prior experience in relevant fields, knowledge of financial concepts, research skills, problem-solving abilities, communication skills, and project management experience.

As a Principal Data Analyst at Capital One, you will leverage analytic and technical skills to innovate, build, and maintain well-managed data solutions and capabilities to tackle business problems. The job involves working on innovation, business intelligence, and data management. The ideal candidate will have a degree in a STEM discipline, scripting experience in Python, R, Spark, and SQL, and strong desire and experience with data in various forms. Basic qualifications include a Bachelor's degree with at least 5 years of experience in data analytics.

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms.

As an Implementation Consultant at Box, you will be responsible for translating business needs into actionable plans, leading complex projects, and building trusting relationships with customers. You will collaborate with multiple teams and provide guidance on improving strategies.

Develop and enhance anomaly detection algorithms using machine learning techniques to improve security features and threat detection in enterprise content management systems.