Data Analyst Supervisor

Job Title:

Data Analyst Supervisor

Salary: $92,808

Job Type: Regular
Full Time

Agency: 695 OKLAHOMA TAX COMMISSION

Supervisory Organization: INN Programs

Posting End Date:
Refer to the date listed at the top of this posting, if available. Continuous if date is blank.

• Generous state‑paid benefit allowance to help cover insurance premiums.
• A wide choice of insurance plans with no pre‑existing condition exclusions or limitations.
• Flexible spending accounts for health care expenses and/or dependent care.
• A Retirement Savings Plan with a generous match.
• 15 days of paid vacation and 15 days of sick leave for full‑time employees the first year.
• 11 paid holidays a year.
• Paid Maternity leave for eligible employees.
• Employee discounts with a variety of companies and vendors.
• A Longevity Bonus for years of service.

The Data Analyst Supervisor will provide data‑driven insights that will significantly impact strategic decision‑making. This role will lead and mentor a team of data analysts, oversee data‑related projects, and collaborate across departments. Responsibilities include assigning and reviewing work, providing training and professional development, and managing the team's schedule and leave.

• Lead, mentor, and guide a team of data analysts, providing regular feedback and conducting performance reviews.
• Provide training, evaluate performance, provide professional development, and manage an assigned team's schedules, time, and leave.
• Assign and prioritize tasks to ensure team deadlines and workloads are balanced.
• Foster a collaborative environment and promote continuous learning and professional development.
• Oversee the analysis of large datasets to extract meaningful insights that support strategic business decisions.
• Develop and implement data analysis processes, including statistical analysis, data mining, and predictive modeling, adhering to industry best practices.
• Design and deliver clear, actionable reports and interactive dashboards for stakeholders at all levels of the organization.
• Ensure data accuracy, integrity, and compliance with applicable standards and regulations.
• Lead data analysis projects from inception to completion, coordinating with cross‑functional teams as needed.
• Ensure alignment of data analysis efforts with business objectives and timelines.
• Identify opportunities for process improvements and streamline workflows.
• Oversee the development of a data warehouse to centralize and standardize tax data from multiple sources.
• Monitor data quality, identify discrepancies, and work with team members to resolve issues.
• Implement data validation techniques to ensure the accuracy and consistency of data used in analyses.
• Establish and maintain data governance protocols and standards.
• Act as a liaison between the data analysis team and other departments (e.g., human resources, tax policy, finance, operations).
• Present findings and insights to executives and key stakeholders clearly and concisely.
• Provide recommendations based on data analysis to guide decision‑making and improve business performance.
• Oversee the use of data analysis tools and software, ensuring the team has access to the necessary resources and training.
• Stay current on industry trends, tools, and best practices in data analytics.
• Perform other duties as assigned.

• Dimensional data modeling techniques and database design principles (normalization, indexing).
• Statistical analysis and data mining techniques.
• Project management methodologies (e.g., Agile, Waterfall) and their application in data analysis projects.
• Experience with data visualization tools such as Tableau, Power BI, Qlik Sense, and Python libraries (Matplotlib, Seaborn).
• Knowledge of data security and privacy best practices.

• Strong analytical and critical thinking skills, including identifying patterns, trends, and anomalies in data.
• Excellent written and verbal communication skills, including effectively presenting technical information to both technical and non‑technical audiences.
• Proficiency in SQL and Python (including libraries like Pandas and Scikit‑learn) for data analysis and manipulation.