GeoPhy is a technology led business focused on providing actionable data, analytics and valuations to commercial real estate institutional lenders and investors in the financial sector. Our technology provides data and insight that helps drive acquisition due diligence, current book monitoring, and site selection review. GeoPhy’s multidisciplinary teams consist of data scientists, engineers, statisticians and economists, using data science and supervised machine learning to optimize the unprecedented volume and variety of data now available in the real estate sector.
We're already working with some of the largest real estate lenders and investors across the globe, and we believe that our AVM will truly disrupt the commercial real estate industry. Using your machine learning and analytical skills, you will contribute to the development of GeoPhy's core information products. This includes working on the development of our flagship product, the Automated Valuation Model (AVM) that we've developed for the commercial real estate market.
What you'll be responsible for
- Developing and maintaining predictive valuation algorithms for the commercial real estate market, based on stochastic modeling.
- Identifying and analyzing new data sources to improve model accuracy, closely working with our data sourcing teams.
- Conducting statistical analysis to identify patterns and insights, and process and feature engineer data as needed to support model development and business products.
- Bringing models to production, in collaboration with the development and data engineering teams.
- Taking the lead in the data sourcing strategy and the validation of related infrastructure and technology.
- Contributing to the development of methods in data data science, including: statistical analysis and model development related to real estate, economics, the built environment, or financial markets.
- Coaching and mentoring other team members in their day to day work.
What we're looking for
- Creative and intellectually curious with multiple years of hands-on experience as a data scientist.
- Experience in industry.
- Direct experience implementing models in production or delivering a data product to market.
- Flexible, resourceful, and a reliable team player.
- Experience in coaching and mentoring other team members.
- Rigorous analyst, critical thinker, and problem solver with experience in hypothesis testing and experimental design.
- Excellent at communicating, including technical documentation and presenting work across a variety of audiences.
- Experienced working with disparate data sources and the engineering and statistical challenges that presents, particularly with time series, socio-economic-demographic (SED) data, and/or geo-spatial data.
- Strong at data exploration and visualization.
- Experienced in designing and implementing predictive models across a full suite of statistical learning algorithms (regression/classification, unsupervised/semi-supervised/supervised).
- Proficient and experienced in Python as well as critical scientific and numeric programming packages and tools.
- Intermediate knowledge of SQL.
- Full working proficiency in English.
- An MSc/PhD degree in Computer Science, Mathematics, Statistics or a related subject, or commensurate technical experience.
Bonus points for
- International mind set.
- Experience in leading technical teams.
- Experience in an Agile organization.
- Knowledge or experience with global real estate or financial markets.
- Experience with complex data and computing architectures, including cloud services and distributed computing.
What’s in it for you?
- You will have the opportunity to accelerate our rapidly growing organisation.
- We're a lean team, so your impact will be felt immediately.
- Personal learning budget.
- Agile working environment with flexible working hours and location.
- No annual leave allowance; take time off whenever you need.
- We embrace diversity and foster inclusion. This means we have a zero-tolerance policy towards discrimination.
- GeoPhy is a family and pet friendly company.
- Get involved in board games, books, and lego.