Junior Data Analyst

It’s more than just numbers.   

Miller Kaplan is a different kind of CPA firm; we believe in building a legacy—yours. We want to give our clients the very best, and we understand that begins with helping our employees be their best through professional mentorship, life-work integration, and a sense of community. That starts with you!

Job Summary:

The Junior Data Analyst in the Data Analytics Department supports both external client engagements and internal practice groups by delivering data-driven insights and solutions. This role offers the opportunity to contribute to high-impact projects, collaborate across teams, and develop analytical expertise within a fast-growing practice area. Success in this role requires the ability to prioritize effectively and perform in a fast paced, deadline driven environment while communicating with the team.

Supervisory Responsibilities:

• None.

Duties/Responsibilities:

• Examine collected data to identify trends, outliers, and patterns, providing actionable insights to enhance client efficiency, profitability, or other specified objectives.
• Gather and organize data from a variety of sources, including departmental heads, subject matter experts, reports, surveys, forecasts, and budgetary documentation, ensuring accuracy and completeness.
• Convert reports into structured databases.
• Design and implement secure, efficient, and accurate databases.
• Perform data cleaning, transformation, and normalization to ensure consistency and accuracy.
• Maintain data integrity and quality controls through validation checks and auditing.
• Assist with query development (SQL) to support reporting and analysis.
• Document database processes, definitions, and data dictionaries for transparency.
• Collaborate with senior analysts or IT teams to support database performance tuning and troubleshooting.
• Ensure compliance with data security, privacy, and access control.
• Assist in developing and maintaining Python scripts to automate recurring data tasks, reporting, and file processing.
• Support the development of ETL workflows that automate data cleaning, validation, and reconciliation to convert raw data into structured, reliable formats.
• Apply basic VBA scripting within Excel to streamline reports, calculations, and client deliverables.
• Document automation steps and maintain clear records for knowledge sharing and future improvements.
• Retrieve, organize, and analyze data from databases to produce accurate and actionable reports.
• Build and maintain interactive dashboards in Power BI, using visualization best practices to highlight key metrics and business trends.
• Develop automated reporting solutions to reduce manual effort and improve reliability.
• Present findings to management and clients with clear, data-driven insights that support decision-making.
• Identify potential strategies to address issues uncovered during data analysis and provide well-reasoned suggestions for improvement.
• Stay current on best practices and emerging trends in data storage, management, and analytics to ensure the firm utilizes state-of-the-art solutions, as well as the ability to apply new knowledge quickly.
• Participate in the planning, execution, and monitoring of data-driven projects, ensuring timely and successful completion.
• Work closely with team members, clients, and other stakeholders to support data-related initiatives and provide actionable recommendations.
• Demonstrate the ability to manage multiple priorities and deliver accurate work in a fast paced, deadline driven environment.
• Perform other related duties and projects as assigned.

Education and Experience:

Required:

• Bachelor’s degree in accounting, Finance, Economics, Data Science, Statistics, Mathematics, Computer Science, Quantitative Analysis, or related field.

Required Skills/Abilities:

• Strong analytical thinking with high attention to detail and accuracy.
• Effective communication and presentation skills for staff and stakeholders at all levels.
• Excellent organizational and time management skills; able to work independently and proactively.
• Proficient in Microsoft Excel (formulas, pivots, Power Query, Power Pivot, DAX, M Code) and the broader Microsoft Office Suite.
• Proficient in programming with Python or SQL.
• Proficient with data visualization tools such as Power BI or Tableau.
• Understanding of database design, structure, and query languages.
• Familiarity with statistical methods (e.g., linear regression, logistic regression).
• Respect for controls