RPOA Advisors Inc
Job Description
Job Description
About Company: Retirement Planners of America (RPOA) is a Dallas-based wealth management and investment firm with over $3.58 billion in assets under management and serving over 6,600 households in 48 states (as of 12/31/23). RPOA has 14 offices in Texas, Arizona, California, and Oklahoma. The firm's financial advisors work with pre-retirees and retirees, offering financial planning, investment management, Social Security planning, and income tax planning services. As a fiduciary-bound firm, we make decisions based on our core values, prioritizing our clients' retirement security. RPOA provides financial planning, investment management, family estate planning and income tax planning services nationwide. We help our clients build a plan to reach their retirement goals while protecting their investment. The RPOA team includes over 30 retirement planners all of them ready to help its clients build a plan to reach their retirement goals while protecting their investments. At RPOA, we believe that retirement should be one of the best times of your life. RPOA’s primary goal is to help our clients to experience the best retirement possible. About the Role: The Analytics and Processing Specialist plays a critical role in transforming raw data into actionable insights that drive strategic decision-making across the organization. This position is responsible for designing, implementing, and maintaining data processing workflows that ensure accuracy, efficiency, and scalability. The specialist collaborates closely with cross-functional teams to understand data requirements and deliver comprehensive analytical solutions that support business objectives. By leveraging advanced analytical techniques and tools, the role contributes to identifying trends, patterns, and opportunities for operational improvements. Ultimately, the Analytics and Processing Specialist ensures that data is effectively harnessed to enhance performance, optimize processes, and support evidence-based strategies. Minimum Qualifications: Bachelor’s degree in Data Science, Statistics, Computer Science, Information Technology, or a related field. Proven experience in data analytics, data processing, or a similar role involving large datasets. Proficiency in SQL and experience with data manipulation and querying. Strong analytical and problem-solving skills with attention to detail. Experience with data visualization tools such as Tableau, Power BI, or similar platforms. Preferred Qualifications: Advanced degree (Master’s or higher) in a relevant discipline. Experience with programming languages such as Python or R for data analysis and automation. Familiarity with big data technologies like Hadoop, Spark, or cloud-based data platforms. Knowledge of machine learning concepts and their application in analytics. Certification in data analytics, business intelligence, or related fields. Responsibilities: Develop, implement, and optimize data processing pipelines to handle large and complex datasets efficiently. Perform detailed data analysis to identify trends, anomalies, and insights that inform business decisions. Collaborate with stakeholders to gather requirements and translate them into technical specifications for data solutions. Maintain data quality by conducting regular audits, validation, and cleansing activities. Create and deliver comprehensive reports and visualizations that communicate findings clearly to both technical and non-technical audiences. Stay current with industry best practices and emerging technologies to continuously improve analytics capabilities. Support the integration of new data sources and tools into existing analytics frameworks. Skills: The required skills enable the specialist to efficiently extract, process, and analyze data to generate meaningful insights that support business goals. Proficiency in SQL and data visualization tools allows for effective querying and clear communication of complex data findings. Analytical and problem-solving skills are essential for identifying data quality issues and optimizing processing workflows. Preferred skills such as programming in Python or R enhance the ability to automate repetitive tasks and implement advanced analytical models. Familiarity with big data technologies and machine learning further empowers the specialist to handle large-scale data environments and contribute to predictive analytics initiatives.
Job Description
About Company: Retirement Planners of America (RPOA) is a Dallas-based wealth management and investment firm with over $3.58 billion in assets under management and serving over 6,600 households in 48 states (as of 12/31/23). RPOA has 14 offices in Texas, Arizona, California, and Oklahoma. The firm's financial advisors work with pre-retirees and retirees, offering financial planning, investment management, Social Security planning, and income tax planning services. As a fiduciary-bound firm, we make decisions based on our core values, prioritizing our clients' retirement security. RPOA provides financial planning, investment management, family estate planning and income tax planning services nationwide. We help our clients build a plan to reach their retirement goals while protecting their investment. The RPOA team includes over 30 retirement planners all of them ready to help its clients build a plan to reach their retirement goals while protecting their investments. At RPOA, we believe that retirement should be one of the best times of your life. RPOA’s primary goal is to help our clients to experience the best retirement possible. About the Role: The Analytics and Processing Specialist plays a critical role in transforming raw data into actionable insights that drive strategic decision-making across the organization. This position is responsible for designing, implementing, and maintaining data processing workflows that ensure accuracy, efficiency, and scalability. The specialist collaborates closely with cross-functional teams to understand data requirements and deliver comprehensive analytical solutions that support business objectives. By leveraging advanced analytical techniques and tools, the role contributes to identifying trends, patterns, and opportunities for operational improvements. Ultimately, the Analytics and Processing Specialist ensures that data is effectively harnessed to enhance performance, optimize processes, and support evidence-based strategies. Minimum Qualifications: Bachelor’s degree in Data Science, Statistics, Computer Science, Information Technology, or a related field. Proven experience in data analytics, data processing, or a similar role involving large datasets. Proficiency in SQL and experience with data manipulation and querying. Strong analytical and problem-solving skills with attention to detail. Experience with data visualization tools such as Tableau, Power BI, or similar platforms. Preferred Qualifications: Advanced degree (Master’s or higher) in a relevant discipline. Experience with programming languages such as Python or R for data analysis and automation. Familiarity with big data technologies like Hadoop, Spark, or cloud-based data platforms. Knowledge of machine learning concepts and their application in analytics. Certification in data analytics, business intelligence, or related fields. Responsibilities: Develop, implement, and optimize data processing pipelines to handle large and complex datasets efficiently. Perform detailed data analysis to identify trends, anomalies, and insights that inform business decisions. Collaborate with stakeholders to gather requirements and translate them into technical specifications for data solutions. Maintain data quality by conducting regular audits, validation, and cleansing activities. Create and deliver comprehensive reports and visualizations that communicate findings clearly to both technical and non-technical audiences. Stay current with industry best practices and emerging technologies to continuously improve analytics capabilities. Support the integration of new data sources and tools into existing analytics frameworks. Skills: The required skills enable the specialist to efficiently extract, process, and analyze data to generate meaningful insights that support business goals. Proficiency in SQL and data visualization tools allows for effective querying and clear communication of complex data findings. Analytical and problem-solving skills are essential for identifying data quality issues and optimizing processing workflows. Preferred skills such as programming in Python or R enhance the ability to automate repetitive tasks and implement advanced analytical models. Familiarity with big data technologies and machine learning further empowers the specialist to handle large-scale data environments and contribute to predictive analytics initiatives.