Sr. Analyst: Workforce Analytics

Level: Senior Analyst

Experience Required: 5+ years in data analysis, workforce analytics, or data science, preferably with experience in professional services, marketing, or related industries.

Key Responsibilities

1. Data Management & Integration

• Collect, manage, and analyze data from multiple sources, including first-party (internal data), third-party (external vendor data), and zero-party (direct employee feedback) sources.
• Ensure data integrity and consistency across various systems, enabling accurate and timely reporting for workforce and operational insights.
• Collaborate with IT and data engineering teams to ensure data pipelines are effectively integrated and optimized for analytics.

2. Workforce Analytics & Segmentation

• Develop and implement data segmentation strategies to categorize and analyze employee behavior, productivity, and utilization metrics.
• Apply advanced analytical methods, including statistical modeling and machine learning techniques, to identify trends, patterns, and areas for improvement within the workforce.
• Provide insights into workforce behavior that drive improvements in capacity planning, utilization, and employee engagement.

3. Data-Driven Decision Support

• Work closely with the Revenue Operations & Resource Management team to provide actionable insights that inform workforce strategy, resourcing decisions, and productivity optimization.
• Develop regular and ad-hoc reports that communicate key findings and recommendations to cross-functional stakeholders, helping them make informed decisions based on data.
• Create and maintain dashboards and visualizations that provide real-time insights into workforce metrics, enabling leadership to monitor progress and trends effectively.

4. Advanced Analytics & Model Development

• Utilize advanced statistical methods and predictive analytics to model employee behavior, engagement, and productivity trends.
• Design and build algorithms to forecast future workforce needs, improve segmentation accuracy, and support long-term strategic planning.
• Stay updated on best practices and emerging trends in workforce analytics, data science, and segmentation, continuously enhancing the analytical toolkit used in the role.

5. Data Storytelling & Senior Management Communication

• Compile complex data sets and analytics into cohesive narratives that clearly convey workforce trends, challenges, and opportunities.
• Present data insights to senior management, creating compelling, data-driven stories that support workforce strategy and decision-making.
• Utilize advanced data presentation tools (e.g., Tableau, Power BI) to visually communicate insights in a clear, impactful way, ensuring that findings are accessible to both technical and non-technical audiences.

6. Cross-Functional Collaboration

• Partner with HR, Finance, and Revenue Operations teams to understand business needs and ensure analytics align with organizational goals.
• Communicate findings and data-driven insights clearly and effectively to both technical and non-technical stakeholders, fostering a data-driven culture within the organization.
• Act as a subject matter expert on workforce analytics, sharing knowledge and mentoring junior team members as needed.

 Key Qualifications

• Educational Background: Advanced degree in Mathematics, Data Science, Statistics, Economics, or a related quantitative field.
• Experience: 5+ years in data analysis, workforce analytics, or a related field, with experience in a professional services or marketing environment preferred.
• Technical Skills: Proficiency in data science and analytics tools (e.g., Python, R, SQL, Tableau, Power BI) with expertise in statistical analysis, data segmentation, and predictive modeling.
• Analytical Expertise: Strong analytical skills with a proven ability to translate data into actionable insights, particularly in understanding and segmenting employee behavior and productivity.
• Communication & Collaboration: Excellent communication skills, with a demonstrated ability to present complex data insights to diverse audiences in a clear, concise manner.