job summary:
Randstad Digital is seeking a Data Analyst/Financial Analyst for an exciting opportunity in Greensboro, NC. This role provides data analysis and strategic insights across our client's commercial dealer channels and pre-owned vehicle sales. Specifically, the position focuses on dealer dashboard performance, management group ownership strategy, and retail sales performance.
location: Greensboro, South Carolina
job type: Contract
salary: $40 - 43 per hour
work hours: 9am to 5pm
education: Bachelors
responsibilities:
This role provides data analysis and strategic insights across our commercial dealer channels and pre-owned vehicle sales. Specifically, the position focuses on dealer dashboard performance, management group ownership strategy, and retail sales performance.
Key Responsibilities
Dashboard Management: Build and manage all critical Power BI dashboards for pre-owned sales and channel development.
Financial Modeling: Develop and maintain driver-based financial models tied to operational metrics.
Performance Analysis: Analyze financial and operational performance, identifying key drivers of variance.
Executive Reporting: Prepare and deliver executive-level reporting, dashboards, and presentations.
Cross-Functional Partnership: Partner with internal teams (operations, sales, leadership) to align financial planning with business objectives.
Profitability Analysis: Perform profitability analysis across products, services, and business units.
Strategic Support: Build scenario models to support strategic decision-making.
Process Improvement: Identify and implement process improvements and automation in reporting and analysis.
Data Integrity: Ensure data accuracy, consistency, and integrity across financial systems.
qualifications:
Required Skills & Competencies
Strong financial modeling and analytical skills.
Ability to translate complex data into clear, actionable insights.
Solid business acumen with a deep understanding of operational drivers.
Excellent communication and presentation skills, especially when presenting to senior leadership.
Strong attention to detail combined with the ability to prioritize high-impact areas.
Problem-solving mindset with a focus on continuous improvement.
High level of ownership and accountability.
Technical Skills / Tools
Excel: Advanced proficiency (modeling, Power Query, VBA preferred).
Business Intelligence: Experience with Power BI or similar BI tools.
Data Science: Working knowledge of Python, R Studio, or other data tools is a plus.
Systems: Experience with ERP and financial systems (e.g., SAP, Salesforce, Oracle, etc.).
Automation: Familiarity with data modeling and reporting automation.
Education & Experience
Bachelor's degree in Analytics, Finance, Economics, or a related field.
Experience in data-driven environments with complex operations is preferred.
Preferred Qualifications
Experience with driver-based planning and scenario modeling.
Background in process automation and reporting optimization.
Exposure to cross-functional or operational finance environments.
Strong understanding of cost structures and profitability drivers.
Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.
At Randstad Digital, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact HRsupport@randstadusa.com.
Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad Digital offers a comprehensive benefits package, including: medical, prescription, dental, vision, AD&D, and life insurance offerings, short-term disability, and a 401K plan (all benefits are based on eligibility).
This posting is open for thirty (30) days.
data analyst.
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