Osaic Careers
Operations Opportunity in Insurance Industry
Data Analyst, Highland Capital Brokerage
Location(s): All Locations/Remote
Role Type: Full time
Salary:$75,000 - $85,000 per year + annual bonus
Actual compensation offered will be determined individually, based on a number of job-related factors, including location, skills, experience, and education.
Summary:
We are looking for a detail-oriented and analytical Data Analyst to join our team. The ideal candidate will be responsible for interpreting data, analyzing results using statistical techniques, and providing ongoing reports. This role requires strong analytical skills, proficiency in data analysis tools, and the ability to communicate findings effectively.
Responsibilities:
Collect, analyze, and interpret data from various sources to identify trends and patterns. Develop and implement data collection systems and other strategies that optimize statistical efficiency and data quality. Perform data analysis using statistical techniques and provide actionable insights. Create and maintain dashboards and reports to visualize data findings. Collaborate with cross-functional teams to understand their data needs and provide solutions. Identify, analyze, and interpret trends or patterns in complex data sets. Work with management to prioritize business and information needs. Ensure data integrity and accuracy by performing regular audits and validations.
Education Requirements:
Bachelor's degree in Statistics, Mathematics, Computer Science, or a related field.
Basic Requirements:
Proven experience as a Data Analyst or in a similar role. Proficiency in data analysis tools such as Excel, SQL, R, or Python. Experience with data visualization tools like Tableau, Power BI, or similar. Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy. Excellent communication skills, both written and verbal. Ability to work independently and as part of a team.
Preferred Requirements:
Master's degree in a related field would be preferred. Experience with big data technologies and tools. Knowledge of data warehousing and ETL processes. Familiarity with machine learning and predictive analytics.
