Top Remote Data & Analytics Jobs in Hartford, CT

As a Data Scientist I, you will help the data team by identifying and managing data sources, utilizing Python, SQL, and R for data scraping and visualization. You will automate data processing, develop machine learning tools, collaborate with various teams, and advocate for best practices in data analysis and visualization.

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 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.

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 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 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.