Top Remote Analytics Jobs in Madison, WI

The Data Integration Specialist will work with clients to onboard their data to Enterra solutions, validate data processes, and communicate requirements. Responsibilities include mapping data, addressing gaps, conducting initial data wrangling, and testing solutions. The role emphasizes collaboration with data engineers and understanding client data needs.

The Data Engineer Consultant at DAS42 is responsible for developing data integrations, implementing data warehouses and ETL pipelines, and optimizing clients' data environments. They work collaboratively on projects, document client data environments, and support the pre-sales process while utilizing technologies like Python and SQL alongside data visualization and cloud platforms.

The Senior Revenue Insights Analyst will drive business growth through data analysis and reporting. Responsibilities include understanding the data needs of the Customer Success organization, creating actionable dashboards, managing projects, and influencing strategic decisions based on business modeling and insights.

The Cyber Threat Hunt Analyst is responsible for creating threat models, planning threat hunt missions, analyzing logs, and reporting risk analysis. This role involves collaborating with teams to enhance threat detection and security posture. Ideal candidates should have experience in network and host analysis and proficiency in scripting languages.

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.

As a Strategy & Analytics Manager at Mission Lane, you will lead initiatives for new products and optimize underwriting and pricing strategies. You'll analyze customer data to improve acquisition and account management, collaborating with cross-functional teams to enhance profitability and customer satisfaction.

As an MLOps Specialist, you will design and implement data systems and architectures to enhance data science processes. Collaborate with data scientists to improve modeling pipelines, build infrastructure, and handle data transformation. This role involves deploying models in production environments, utilizing cloud services like AWS, and supporting a team-oriented culture.