What are the responsibilities and job description for the Lead Associate, Data Management position at BetaNXT Inc?
About BetaNXT
BetaNXT powers the future of connected wealth management infrastructure solutions, leveraging real-time data capabilities to enhance the wealth advisor experience. Combining industry expertise with the power of our proven Beta, Maxit, and Mediant businesses, we are focused on solving our customers’ most demanding integration challenges with flexible, efficient, connected solutions that anticipate their changing needs. Our comprehensive approach reduces enterprise cost, streamlines operations processes, increases advisor productivity, and enhances the investor experience. Together with BetaNXT, wealth management firms are transforming their platforms into differentiating assets that enable enterprise scale and stimulate commercial growth. For more information visit www.betanxt.com.
Overview:
The Performance Metrics Analysis is responsible for transforming vast amounts of data into actionable insights. This role is crucial for the organization, ensuring that key performance indicators (KPIs) are accurately tracked and presented, enabling informed decision-making processes. Proficiency with advanced Excel skills is indispensable for performing these duties efficiently.
Key Responsibilities
1. KPI Development and Monitoring
- · Design and implement comprehensive KPIs that align with the organizational goals and objectives.
- · Regularly monitor and update KPI metrics to reflect any changes in strategic direction.
- · Create dynamic dashboards and reports that provide real-time insights into KPI performance.
2. Data Collection and Management
- · Aggregate data from various internal and external sources ensuring accuracy and consistency.
- · Maintain a centralized database for all KPI-related data, ensuring it is up-to-date and accessible.
- · Streamline the data collection process to minimize manual effort and maximize efficiency.
3. Advanced Excel and PowerBI Utilization
Utilize advanced Excel functions such as VLOOKUP, pivot tables, macros, and statistical tools to manipulate and analyze data.
Leverage PowerBI to create interactive and visually appealing dashboards that provide real-time insights.
Create automated Excel templates and PowerBI reports that standardize reporting and minimize errors.
Train team members on advanced Excel techniques and PowerBI functionalities to enhance their data handling capabilities.
4. Statistical Analysis and Reporting
- · Perform detailed statistical analyses to uncover trends, correlations, and anomalies in the data.
- · Generate comprehensive reports that summarize key findings and provide actionable recommendations.
- · Present statistical reports to stakeholders, ensuring they understand the implications of the data.
5. Continuous Improvement
- · Identify opportunities to enhance KPI tracking and data analysis processes.
- · Stay updated with the latest industry trends and best practices in data analytics and KPI management.
- · Implement new tools and technologies that improve data accuracy, efficiency, and reporting capabilities.
Required Skills and Qualifications
- · Advanced proficiency in Excel, including the use of complex formulas, pivot tables, and macros.
- · Strong analytical skills with the ability to interpret and present data effectively.
- · Experience in developing and monitoring KPIs within a business context.
- · Excellent attention to detail and commitment to data accuracy.
- · Strong communication skills to convey complex data insights to non-technical stakeholders.
- · Proficiency in Power BI, including data modeling, DAX, and creating interactive dashboards.
- · Bachelor’s degree in a related field such as Business Analytics, Statistics, or Data Science.
- · Experience with other data visualization tools like Tableau is an advantage.
- · Ability to work independently and collaboratively within a team environment.
Performance Metrics
- · Accuracy and timeliness of KPI reports and dashboards.
- · Quality and clarity of statistical analyses and findings.
- · Efficiency of data collection and management processes.
- · Level of stakeholder satisfaction with KPI insights and recommendations.
- · Adoption and effectiveness of Excel templates and automated reports.