3-4 years of experience in commercial real estate, focusing on data analysis.
Proficiency with BI/visualization tools, particularly Looker.
Demonstrated experience in QA or data quality assurance.
Strong communication skills for both technical and client-facing interactions.
Ability to quickly learn new technical tools and domains.
Nice to have: Familiarity with LookML, dbt, or data warehousing; prior experience in AI/LLM QA; knowledge of lease or CRE contract structures.
Responsibilities
Apply commercial real estate expertise to train and maintain AI tools.
Support QA and migration of client-facing BI dashboards to a new data warehouse.
Build and troubleshoot dashboards in Looker for client insights.
Collaborate with product, engineering, and client teams to address data quality issues.
Develop deep expertise in VTS's AI tools, data, and client dashboards.
Benefits
Work at the intersection of AI, data, and commercial real estate.
Gain direct exposure to strategic AI initiatives and client dashboards.
Enjoy real ownership over data accuracy and model performance.
Opportunities for growth as VTS's AI and analytics capabilities expand.
Full Job Description
In this role, the Analyst will join the Data Solutions team, serving as a domain-expert QA layer between VTS's AI engineering initiatives and its client-facing analytics. The Analyst will apply commercial real estate knowledge to help ensure the data our AI systems learn from, and the dashboards our clients rely on, are accurate and trustworthy.
** Please note that this opportunity is located in New York, NY, and requires this hire to work from our office 4 days a week. **
What you can expect as a Data Solutions Analyst:
Apply commercial real estate knowledge to assist in training, launching, and maintaining VTS's AI tooling.
Support the QA and migration of client-facing BI dashboards to a new data warehouse.
Build, maintain, and troubleshoot dashboards in Looker to help deliver insights to clients.
Partner with product, engineering and client-facing teams to resolve data quality issues.
Develop deep domain expertise across VTS's AI tooling, data, and client dashboards.
What makes this job awesome:
Working at the intersection of AI, data, and commercial real estate.
Direct exposure to VTS's most strategic AI initiatives and client-facing dashboards.
Real ownership over the accuracy of what ships to clients and how our models perform.
Room to grow as VTS's AI and analytics footprint scales.
What makes you a great fit?
3-4 years of experience in commercial real estate, including analyzing CRE data.
Experience with a BI/visualization tool such as Looker.
A track record of meticulous, structured QA or data-quality work.
Strong communication skills across technical and client-facing audiences.
Comfortable working in technical tooling and picking up new domains quickly.
Nice to have: LookML, dbt, or data warehouse experience; prior AI/LLM QA exposure; familiarity with lease or CRE contract structures.
Pay Transparency
At VTS, we pride ourselves on articulating a clear and transparent philosophy around equitable, impartial compensation that will allow us to recruit and retain an exceptional team. The base salary is market-driven at the time of offer and is based on tier 1 market data. The salary for this role will range between $110,000 and $125,000 and is determined by several factors, including your skills, prior relevant experience, quality of interviews, leveling, and geography.
About VTS
VTS is a commercial real estate technology platform that provides leasing and asset management software to landlords and brokers. The company was founded in 2012 and is headquartered in New York City. VTS has over 10 billion square feet of commercial real estate space on its platform and serves over 700 customers worldwide. The platform allows landlords and brokers to manage their leasing and asset management activities in one place, providing real-time data and analytics to help them make informed decisions. VTS has raised over $300 million in funding from investors such as Blackstone, Brookfield, and Fifth Wall.
