PrimePay makes payroll and HR complexity disappear for small and midsize businesses. We've packaged 37 years of experience and an unrelenting commitment to service into an intelligent, versatile HCM platform.

A platform defined by options and designed to deliver exceptional "I can't believe how simple that is" experiences for HR and finance pros and every employee.

More than 18,000 clients rely on the PrimePay Platform to replace manual work, replace compliance worries, and stop wasting time on things that should just work, so they can get back to work.

Do you love to build, innovate, create and collaborate? Come grow your career and make an impact with PrimePay - a growth focused, flexible and established Human Capital Management (HCM) SaaS technology company.

As we continue our evolution and growth into a leading HCM SaaS technology provider to businesses, we are seeking our next Data Analyst. The Data Analyst plays a pivotal role in supporting operations and conducting data analytics projects. The primary objective is to provide actionable insights to stakeholders for decision-making and solution development. This role involves implementing data standards, deploying automation tools, and ensuring data integrity through monitoring and troubleshooting database issues.

At PrimePay, we are seeking those excited to build, create, and innovate. We are problem-solvers who move quickly, collaborate with agility and differentiate through people, purpose and commitment. With a 30+ year history, we are writing the next chapter of our journey with a focus on great technology, a People First Culture and a commitment to personal and professional growth. At PrimePay, our extraordinary people create our future every single day. Interested? Join us in our evolution!

Responsibilities:

• Lead or assist in managing data analysis projects from inception to completion. This involves defining project scope, objectives, timelines, and deliverables in coordination with stakeholders. Ensure adherence to project milestones and deadlines
• Develop and implement data standards and best practices to ensure consistency, accuracy, and integrity across datasets. Collaborate with relevant teams to establish and maintain data governance policies
• Identify opportunities for automation in data extraction, synthesis, and validation processes. Implement automation tools and workflows to streamline repetitive tasks and improve efficiency
• Oversee database management activities including data storage, retrieval, and security. Proactively monitor data quality and troubleshoot database issues to prevent disruptions and ensure uninterrupted access to data
• Utilize scripting languages such as Python, R, and SQL to manipulate, analyze, and extract insights from large datasets. Develop and optimize queries to extract specific information relevant to stakeholders' needs
• Design and develop visually appealing dashboards, reports, and data visualizations using BI analytics and reporting tools. Present complex data in a clear and understandable manner to facilitate decision-making
• Collaborate closely with stakeholders including business users, analysts, and decision-makers to understand their requirements, objectives, and challenges. Translate business needs into actionable insights and data-driven solutions
• Stay abreast of industry trends, emerging technologies, and best practices in data analytics. Continuously enhance skills and knowledge through self-learning, training, and participation in professional development activities
• Maintain documentation related to data analysis processes, methodologies, and findings. Share knowledge and insights with team members to foster a culture of collaboration and knowledge exchange
• Conduct thorough quality assurance checks on data analysis outputs to ensure accuracy, completeness, and consistency. Implement validation protocols and procedures to validate data accuracy and integrity
• Provide ad hoc data analysis support to address urgent business needs or inquiries. Quickly analyze data, identify trends, and generate actionable insights to support decision-making in real-time scenarios
• Collaborate with cross-functional teams such as IT, finance, marketing, and operations to integrate data analytics into various business processes and functions. Identify opportunities for synergy and collaboration to maximize the impact of data insights

Qualifications

• Bachelor’s degree in business, a quantitative field, or equivalent
• 0-2 years of relevant experience
• Demonstrate proficiency in using a variety of business intelligence (BI) analytics and reporting tools such as Tableau, Power BI, or QlikView. Ability to leverage these tools to extract, analyze, and visualize data effectively
• Possess hands-on experience in designing and configuring interactive and user-friendly dashboards. Ability to customize dashboards to meet specific business requirements and present data in a visually compelling manner
• Strong understanding of data mining techniques and algorithms. Ability to apply data mining methods to discover patterns, trends, and insights from large datasets, driving actionable business recommendations
• Experience in implementing data quality assurance processes and methodologies. Ability to assess data quality issues, develop strategies for data cleansing and validation, and ensure data accuracy and consistency
• Familiarity with a wide range of data visualization techniques such as charts, graphs, heatmaps, and infographics. Ability to select the most appropriate visualization method to effectively communicate insights and findings
• Proficiency in performing forecasting and predictive analytics using statistical methods and machine learning algorithms. Ability to build predictive models, analyze trends, and generate accurate forecasts to support decision-making
• Strong programming skills in scripting languages such as Python, R, and SQL. Ability to write efficient scripts and queries to manipulate, analyze, and extract insights from complex data sets
• Solid understanding of statistical analysis concepts such as hypothesis testing, regression analysis, and probability distributions. Ability to apply statistical techniques to analyze data and derive meaningful insights
• Experience in conducting trend analysis to identify patterns, anomalies, and correlations in historical data. Ability to extrapolate trends and make informed predictions about future outcomes
• Familiarity with industry-standard data standards and protocols. Proficiency in using statistical software packages such as SPSS, SAS, or Stata for advanced data analysis and modeling
• Proficiency in using general data analysis software such as Microsoft Excel, Google Sheets, or MATLAB. Ability to perform basic data manipulation, analysis, and visualization tasks using these tools