Sr Data Analyst

September 4

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NationsBenefits

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NationsBenefits is a leading member engagement, benefits administration, and healthcare company that partners with managed care organizations to provide innovative healthcare solutions aimed at driving growth, reducing costs, and delighting members$1. .$1

1001 - 5000

💰 Private Equity Round on 2022-04

Description

• Collect, clean, and analyze large datasets to identify trends, patterns, and insights that inform business decisions. • Create compelling and informative data visualizations using tools like Tableau, Power BI, or similar to effectively communicate findings to stakeholders. • Develop and maintain automated and ad-hoc reports and dashboards to track key performance indicators (KPIs) and provide regular updates to management. • Apply statistical techniques to perform hypothesis testing, regression analysis, and other advanced analyses to support decision-making. • Ensure data accuracy, consistency, and reliability through data validation and cleaning processes. • Work closely with cross-functional teams, including marketing, product development, finance, and operations, to provide data-driven insights and support decision-making. • Provide actionable recommendations based on data insights to drive continuous improvement and optimization of processes and strategies. • Maintain clear and organized documentation of data analysis processes, methodologies, and findings. • Keep abreast of industry trends, emerging tools, and best practices in data analysis to continuously improve skills and methodologies.

Requirements

• Bachelor's degree in a related field (e.g., Statistics, Mathematics, Computer Science, Business Analytics). • 5+ years of experience as a Data Analyst, with a proven track record of delivering actionable insights. • Expert level skill in SQL, plus experience with Python and/or R. • Strong data visualization skills using tools like Tableau, Power BI, or similar. • Excellent problem-solving and critical-thinking abilities. • Strong communication skills, with the ability to present complex findings to non-technical stakeholders. • Attention to detail and a commitment to data accuracy. • Experience working with large datasets and knowledge of database management systems. • Knowledge of statistical analysis techniques.