Financial Reporting-Associate

Job description

Divisional overview

The Controllers group is responsible for safeguarding the firm's assets: to help maintain the integrity of Goldman Sachs' finances and expenditures.

Through careful consideration and analysis of firm finances, objectives, and strategies, we ensure that the firm's businesses continue to be profitable and efficiently run. Controllers also ensure that all business practices are in compliance with financial and regulatory requirements worldwide. Since contact with virtually every part of the firm is essential to Controllers, professionals in the department experience Goldman Sachs businesses, products, and sophisticated technology systems in depth.

Responsibilities

• Preparation of daily and weekly reports on a rotation basis.
• Produce monthly, quarterly, and ad-hoc financial reports.
• Review and analysis of financial performance and trends.
• Review and analysis of business unit, divisional and regional profitability, and efficiency.
• Analyze operating expenses and provide monthly and quarterly expense analyses.
• Contribute to month-end and quarter-end processes.
• Assist with the development and maintenance of annual budgets and forecasts.
• Preparation of various month-end reporting packs.
• Work closely with other areas of the firm, including Regulatory Reporting, Corporate Accounting, Technology, and Revenue - Producing Division.
• Manage ad-hoc requests.

Basic Qualifications

• Qualified CA & MBA.
• Basic industry knowledge and strong accounting knowledge. Keen interest in products and markets and a flair for systems.
• Strong communication and interpersonal skills.
• Strong analytical skills.

Preferred skills

• The candidate must be proactive, enthusiastic, and team-oriented.
• Ability to prioritize and make decisions in a fast-paced environment.
• Accuracy and attention to detail.
• Understanding accounting tools such as Hyperion Essbase would be an added advantage.
• Strong PC (Excel, PowerPoint, and MS suite) skills including advanced data mining techniques.