Financial Analyst - Night Shift

Job not on LinkedIn

February 16

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System Soft Technologies

System Soft is an IT service management company. We solve IT challenges of your limited managed IT services, which can hinder you from accomplishing technology solutions goals. We act as an extension of your IT team, providing everything from project support to complete IT consulting to future-proof your infrastructure. We invest in innovative technology solutions and methods to enhance your business agility, value and competitiveness.

501 - 1000 employees

📋 Description

• Establish budgets, lead forecasting, collect required information, distribute financial metrics, and provide performance insights • Collaborate with company leaders, project managers, and IT team to analyze and distribute information • Track and project profit margins for upcoming quarters • Analyze trends, notify leadership of anomalies, and prepare cost forecasts • Analyze financial reports to identify cost-effective improvements • Collect and organize cost and revenue information into a database • Determine fixed and variable costs • Work with leadership to formulate medium to long-term financial and strategic plans • Provide insights around financial modeling, forecasts, and profitability • Conduct periodic audits of budget items • Generate monthly financial reports

🎯 Requirements

• Bachelor's degree in finance, accounting, or related business discipline • Ability to create and manage budgets and facilitate forecasting • Excellent written and verbal communication skills • Proficient in Microsoft Office Suite or related software, as well as budget creation and analysis software • Thorough understanding of budgetary and accounting principles, practices, and policies • Advanced computer software skills, including writing macros in Excel and other accounting packages • Knowledge of IT consulting and Project services, staffing and technology platforms • Three to five years of work experience in a financial role • Experience modeling and manipulating large sets of data

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