Benefits Systems Analyst - Healthcare jobs in Grand Prairie, TX

Job Purpose:
As a Data Analyst, your primary responsibilities will be to analyze commission-related data as well as efficiently collecting/processing data to drive business decisions and optimize processes. By leveraging your analytical skills and proficiency in programming languages and data visualization tools, you will collaborate with cross-functional teams to identify trends, patterns, and opportunities for improvement. Your contributions will directly impact the company's commission processes and overall business performance.

Responsibilities:

• Analyze commission-related data and commission reports to identify and resolve discrepancies between expected and actual commissions.
• Investigate revenue results, providing comprehensive explanations for variances to forecasts.
• Collaborate effectively with leadership to enhance commission processes and drive improvements.
• Collect and process large datasets efficiently.
• Conduct statistical analyses to uncover trends and patterns within the data.
• Develop and present visualizations and dashboards to effectively communicate findings to stakeholders.
• Build predictive models to support decision-making processes.
• Identify opportunities to optimize business processes based on data insights.
• Collaborate with cross-functional teams to develop and implement data-driven solutions.
• Perform other duties as assigned by management.

Requirements:

• Strong ability to work collaboratively with cross-functional teams.
• Proficiency in programming languages such as Python and R, with experience interacting with SQL and NoSQL databases.
• Demonstrate analytical and problem-solving skills.
• Proficiency in data visualization tools such as Tableau and Power BI.
• Excellent communication and presentation skills.
• Attention to detail and ability to identify and address data quality issues effectively.

Preferred Qualifications (not required but beneficial):

• Experience with commission-related data analysis.
• Familiarity with financial forecasting and revenue analysis.
• Knowledge of machine learning techniques and algorithms.
• Previous experience in process optimization initiatives.