Top Remote Data & Analytics Jobs

As a Staff Data Scientist, you will develop statistical and machine learning models to enhance the operations platform. Responsibilities include leveraging data to solve problems, collaborating across teams, implementing predictive models, and mentoring teammates. Excellent communication and technical skills are essential, along with a strong background in Python and statistical software.

The Data Operations Manager will oversee data operations for sales and sales development, ensuring the revenue engine's scalability. This role involves managing a team, analyzing sales data, and implementing operational improvements to enhance efficiency and performance in achieving sales targets.

As an Ad Hoc Data Processing/Data Entry Specialist, responsible for accurately entering and processing data according to company's standards and procedures. Requires high attention to detail, efficiency, and handling confidential information.

The Sr. Data Scientist at DataRobot will act as a trusted advisor on AI for US Federal Government entities. Responsibilities include leading technical engagements, demonstrating the DataRobot product, and collaborating with customers to implement AI solutions that drive business value. The role requires expertise in machine learning and strong customer-facing skills.

The Senior Information Security Analyst II will develop and execute a global compliance strategy, ensuring adherence to regulations like PCI, SOC 2, and GDPR. Responsibilities include leading audits, maintaining security policies, managing compliance projects, and addressing customer security concerns in collaboration with teams like Engineering and Sales.

The Data Acquisition Specialist will source, collect, and maintain accurate data to support semiconductor distribution. Responsibilities include evaluating data sources, implementing data collection methods, ensuring data quality, conducting analysis and reporting, and collaborating across departments. The role also promotes continuous improvement in data practices.

The role involves architecting, building, and maintaining reliable data pipelines, developing data applications in Python and SQL, ensuring data quality, and optimizing software engineering techniques while collaborating with IT and business teams.