Michael Cohen joined PriceHubble as Head of Data Science in March 2022. We have talked with Michael about his impressions and experiences during his first 100 days.
Describe your first 100 days in three words.
Enriching. Fascinating. Intense.
What is your impression of PriceHubble after your first 100 days?
PriceHubble is a motivating, fast-paced and welcoming environment. One of the most impressive aspects is how the company manages to be at the forefront of innovation and real estate valuation in so many different countries, in spite of their local specificities in terms of real estate market, available data or legal frameworks.
What is the role of head of data science?
It is manyfold! At a high level, it goes from designing the Data Science roadmap with our Product organisation, to guiding Data Scientists through their professional development journey, while driving efforts around team growth or Machine Learning architecture.
But looking at more specific aspects, it also involves data quality and security (a key part of the data area), supervising model reliability processes or ensuring our ML platform’s scalability.
What exactly is your team doing and which teams do you work with?
The Data Science team (that we call «Value», internally) is delivering PriceHubble’s automated valuation models for real estate properties. In practice, it means that our Machine Learning models infer the value of any property in countries where PriceHubble is doing business.
It doesn’t stop there, however. The Data Science team is also owning the «Real Estate Insight» data products at PriceHubble. This can be about analysing the property's price sensitivity to specific data fields, or delivering «price maps» that help our customers visualise which geographical areas are hotter than the others–real estate-wise!
Our main collaborators are the Data Product and the Data Engineering teams. But everyone collaborates at PriceHubble, so we can also interact with the countries’ Managing Directors, DevOps teams or Business Intelligence groups, for instance. And, look at this Q&A, with our communication team too!
What characterises the work of PriceHubble's data science team? Is there anything that is different from your previous experience in this field?
At PriceHubble, Data Scientists have a very strong engineering culture, and this is reflected in their day to day work. In some organisations, Data Science can be just about creating reports, prototyping models and handing them over to another production team. At PriceHubble, it’s different: Data Scientists work with many different frameworks and stacks and are enabled to actually go to production with their models. This offers them a very gratifying sense of ownership.
What surprised you during your first 100 days at PriceHubble?
I was extremely happy to see how committed the teams are in order to keep the whole organisation successful. Every day, I work with engineers dedicated to their mission and who want to see their team deliver the best products available on the market.
Is there anything else you would like to say about PriceHubble?
It’s a company that brings together many cultures, with offices everywhere in Europe, and people that come from all over the world. But it’s also a group of happy and energetic individuals, who want to team up, be bold and contribute to the automation of the real estate valuation world!
Understanding real estate valuation methods is crucial for evaluating residential and commercial properties. Real estate agents use this knowledge to set selling or rental prices. That way, they ensure successful sales, meeting the seller's goals. Mortgage lenders and investors also find it essential to comprehend these methods. Experts in real estate investment need property valuations for informed decision-making. Selecting the right investment property is crucial for their rate of return.
The European real estate landscape is undergoing significant changes: heightened market fluctuations, surging inflation, and escalating interest rates. This landscape makes it complex for investors to find secure, diversified, and stable investment avenues. The emergence of ESG and sustainability-related topics presents a challenge to making informed and wise investment decisions. In this dynamic environment, real estate asset management in the housing market is gaining considerable relevance.
