Applied Data Scientist, CompStak
Econometrics
$120-160k
3 days a week in office
Commercial real estate data platform
Job no longer available
Commercial real estate data platform
101-200 employees
Job no longer available
$120-160k
3 days a week in office
101-200 employees
Company mission
To help create a commercial real estate industry in which accurate and transparent data leads to better, faster deals for everyone.
Role
Who you are
- We are seeking an Applied Data Scientist – Econometrics with a strong foundation in economics, econometrics, finance, or commercial real estate and an interest in applying quantitative modeling to real-world market behavior
- This role is ideal for someone who understands how markets work, has experience working with data, and wants to apply (and grow) modern analytical and data science methods within a commercial real estate context
- 3+ years of experience in an econometrics-focused or analytical role (e.g., economics research, finance, market analysis, consulting, commercial real estate, or corporate strategy)
- Strong understanding of econometrics, applied statistics, and quantitative modeling, demonstrated through academic or professional experience
- Proficiency in Python and familiarity with analytical/ML libraries (pandas, NumPy, scikit-learn, XGBoost)
- Experience working with large or complex datasets and using data to study market dynamics
- Excellent organizational, communication, and stakeholder management skills
- Bonus: Hands-on experience or interest in LLMs, embeddings, NLP tools, or modern ML frameworks (e.g., Hugging Face, LangChain, PyTorch/TensorFlow)
- Bonus: Experience working in commercial real estate, PropTech, or investment analytics
What the job involves
- In this role, you will help shape how CompStak analyzes, models, and interprets market dynamics by combining domain expertise with econometric and quantitative techniques
- Apply econometric and statistical modeling to analyze and forecast trends in commercial real estate and related economic drivers
- Learn and apply modern analytical and machine learning techniques as needed to enhance insights and support CompStak’s data products
- Build scalable workflows that integrate structured CRE datasets with new, unstructured sources to support data enrichment and automation
- Collaborate closely with engineering, product, and data teams to develop data-driven solutions
- Bridge domain knowledge and quantitative methods to deliver models that are accurate, interpretable, and meaningful for business decisions
- Develop econometric and predictive models: Use quantitative methods to identify patterns, forecast trends, and interpret economic relationships in CRE markets
- Build and optimize data workflows: Create and refine data ingestion and transformation pipelines for structured and unstructured commercial real estate datasets
- Ensure data quality: Clean, validate, and reconcile datasets from diverse sources to ensure accuracy and reliability
- Communicate insights: Translate complex quantitative analysis into clear, actionable insights for both technical and non-technical stakeholders
- Stay current: Keep up with developments in econometrics, applied analytics, and trends in CRE markets and data science
Our take
When it comes to renting commercial property and office spaces, many businesses face a lack of pricing transparency. CompStak leverages world-class commercial real estate data to solve this problem.
CompStack has enjoyed considerable success by marketing its data, which gives users a more reliable idea of commercial property values, to landlords, real estate agents and tenants alike. CompStack has also benefited from being one of the first wave of proptech companies that appeared in the 2010s. Since then it has become an established force in the market, with clients including Allianz and PwC.
The company has substantial funding behind it, which is clear proof that the it has maintained its solid footing in the proptech market. To stay ahead of emerging competitors, it will be essential for the company to leverage this money to drive further innovation and continue building on its success.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
47% employee growth in 12 months
Company
Funding (last 2 of 8 rounds)
Nov 2021
$50m
SERIES C
May 2019
$12m
SERIES B
Total funding: $98.3m
Company HQ
Chelsea, New York, NY
Leadership
Michael Mandel
(Co-Founder & CEO)Previously worked as New York Metro Leader at Grubb & Ellis, and has seen a TechStars mentor since 2016.
Vadim Belobrovka
(Co-Founder & CTO)Previously worked as a Tech Team Lead at UBS, and as a Software Engineer at Corbin Capital Partners. Then joined CRT Capital Group as Senior Software Engineer.
Salary benchmarks
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