Top Entry Level Analytics Jobs

As a Quantitative Researcher at Aquatic, you will collaborate to develop and implement quantitative trading signals and models. The role involves designing, implementing, and evaluating systems using statistical methodologies while gaining expertise in quantitative finance.

The Data Analyst is responsible for inputting and managing data within the company's management systems daily, providing accurate inventory information, and ensuring the smooth flow of warehouse operations while adhering to standard operating procedures. Additional responsibilities include the classification of documents, data statistics, and other tasks as assigned by management.

The Data Analyst will analyze data and generate insights to support business decisions. Responsibilities include conducting full lifecycle analysis, developing reporting capabilities, and maintaining databases. The analyst will interpret data trends, implement data collection strategies, and provide ongoing reports.

As a Data Entry Specialist at Carvana, you will handle the administrative tasks for vehicle ownership registration, ensuring documentation is accurate and processes are completed efficiently. This role involves problem-solving and communication with customers to provide a seamless experience in vehicle registration.

The Technical Service Analyst will troubleshoot technical issues, maintain integrations between RELEX systems and customer backends, and support escalations from the first line support team, while communicating with both internal and external stakeholders to enhance service quality.

The Benefit Analyst role involves managing benefit-related inquiries, collaborating with brokers and administrators, conducting quality assurance for benefit builds, maintaining dashboards, and building EDI files. The role requires strong communication and problem-solving skills and technical knowledge to troubleshoot and resolve issues with carriers.

The Associate Data Analyst will support custom analytics deliverables, collaborate with data scientists and client-facing teams, fetch and analyze data using SQL, Python, and BI tools, and develop positive relationships with stakeholders and clients.