- Entry level
- No Education
- Salary to negotiate
GeoPhy is a technology company in the real estate space. We provide property valuations engineered for the modern world, giving property lenders and investors fast, consistent and reliable access to information. Our technology allows our customers to understand value and its drivers by using both traditional and unconventional sources, using machine learning to create the most accurate valuations in the market.
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.
As a Senior GIS Data Engineer for Contextual Data at GeoPhy, you work on the collection, structuring and analysis of "contextual" data sources that will help advance our ValueDrivers and Automated Valuation Models products, enabling us to better serve our customers in the commercial real estate industry. You have experience in the geospatial domain and in addition to your strong technical background, you are a natural communicator who is able to explain complex data and engineering issues to business and data science teams.
What you'll be responsible for
As a Senior GIS Data Engineer for Contextual Data, you will help the team to engineer automated pipelines to deliver data into our platform. You build out an analytics data suite, developing data layers that power question our ValueDrivers and Automated Valuation Models (AVMs). You will be at the nexus of data science and business at a company that is changing the commercial real estate industry. Your responsibilities will include:
- Source, engineer and analyze novel sets of data and features that reflect the dynamics of the commercial real estate market.
- Creation of indexes and features for the AVM.
- Data wrangling and transformation in SQL/Postgresql databases. Gis
Spatial data transformation (postgis) and visualisation (QGIS and mapbox).
- Using Python to scrape websites to construct valuable datasets.
- Cleaning/transforming scraped data.
- Building indexes based on multiple data sources (accessibility index, vibrancy index, liveability index etc.) Data enrichment
- Enriching basic datasets with contextual data from various sources.
- Analysing the enriched dataset and providing statistical insight on the results.
- Visualize data in intuitive and clear ways. What we're looking for
- Degree in Computer Science/Engineering, Mathematics, Statistics, Economics, or another quantitative field; advanced degree is desirable.
- Proficiency in GIS.
- 2+ years Python, SQL and Postgres+Postgis experience.
- Experience with feature engineering for machine learning models.
- Affinity with real estate and the built environments.
- Passion for "cool" and useful sources of contextual data. Bonus points for
- Experience in the (commercial) real estate sector.
- Experience with Kafka/K8s and streaming of geospatial data.
- Experience with Spatial indices and spatial query optimization.
- Experience with geospatial deduplication.
- Experience in Software engineering (python). What's in it for you?
- The opportunity to accelerate our rapidly growing organization.
- We're a lean team, so your impact will be felt immediately.
- A Personal learning budget.
- No annual leave allowance; take time off whenever you need.
- Agile working environment with flexible working hours and location, career advancement, and competitive compensation package.
- Diverse, unique colleagues from every corner of the world.
- A family and pet friendly company.
- Board games, books, and lego.
- real estate