Asset Manager Job at Cobalt Recruitment, Nassau County, NY

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  • Cobalt Recruitment
  • Nassau County, NY

Job Description

Asset Manager

Nassau County, Long Island, New York (On-site)

$75,000 - $95,000 plus discretionary performance bonus

Overview:

The Asset Manager will be responsible for managing business plan execution, financial performance, tenant relations, and operational efficiency in the region. The ideal candidate will have experience in real estate investment, asset management, and a strong understanding of the commercial real estate market.

Key Responsibilities:

  • Asset Optimization: Develop and implement business plans to analyze and optimize the asset operational performance including lease audit and chargebacks, including setting annual budgets, forecasting property level cash flows, and conducting detailed financial analysis to maximize return on investment.
  • Market Analysis: Conduct market research to assess property values, trends, and competitive positioning. Develop strategies to enhance asset performance including property upgrades and repositioning.
  • Reporting & Communication: Provide regular performance reports to senior leadership, including detailed financial analysis, occupancy trends, leasing activity, progress on key initiatives, and quarterly valuations.
  • Collaboration: Work closely with acquisitions, property management, legal, lease administration, accounting, and finance to optimize portfolio performance.

Qualifications:

  • Proficiency using Advanced Excel functions for data management and analytics.
  • Bachelor’s degree in finance, business, economics, real estate, or a related field.
  • 3-5 years of experience in the commercial real estate field, functioning as an Asset Manager.
  • Excellent ability to analyze operations across a portfolio of commercial real estate.
  • Solid understanding of real estate operations, utility auditing and cam reconciliations and other key performance drivers.
  • Excellent presentation and analytical skills.
  • Manage, organize and analyze large data sets
  • Self-motivated, eager to learn, detail-oriented, and able to work with minimal supervision.

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