Data Scientist

Data Scientist

Chicago, IL (remote until after COVID)

If you have ever enjoyed or considered applying data science to understand the giant, tangled world of real estate – the world's largest asset class – consider this: there is almost nowhere else you could work where you would have access to a greater depth and variety of private data used every day to drive decisions. The global, cross-asset, constantly growing scope of Blackstone's real estate portfolio means endless opportunity for impact at scale. Different portfolio companies are in different stages of their data journey, and while all of them understand that data science is valuable, not all of them know how specifically it could help them. Thus, bookending the "data science" itself, you will be responsible for communicating with stakeholders, deeply understanding their business problems, and creatively determining how to solve those problems with data science. In the bigger picture, you will be responsible for helping to grow demand for data science services. You will, of course, also be responsible for performing advanced statistical/machine learning modeling and analysis across real estate market, customer (tenant), investment and other asset domains to provide insights for Blackstone and its portfolio companies.

Our Team Data Science culture prioritizes care, transparency, creativity, working smarter over harder (while understanding that sometimes "harder" is necessary), iterative delivery, async-first communication, and compounding team practices that enable constant learning and make us greater than the sum of our parts (some examples: paired programming rotations, 1:1s, retrospectives, weekly open-ended discussions). Above all, we care about giving you the tools and space you need to do your best work.

What You'll Be Doing

• Research and implement cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence to make data analysis more efficient and meaningful
• Provide input on new use cases, capabilities, and initiatives to inform the Data and Analytics strategic roadmap development and execution
• Develop frameworks and processes to analyze unstructured information collected through internal and external data sources
• Enhance information visualization through development of dashboards and user interfaces
• Establish best practices for data-based experimentation across Technology teams
• Leverage current analyses and communication skills to grow demand from existing and new stakeholders
• Contribute actively to the culture of constant learning, experimentation, and improvement within and beyond Team Data Science.

Skills We're Seeking

• Bachelor's degree in Computer Science, Business, Economics, Accounting, Engineering or related field, or demonstrable equivalent aptitude for statistics, machine learning and programming
• 3+ years of experience using machine learning algorithms and statistical analysis techniques (e.g., Regression, Classification, Naïve Bayes, Support Vector Machines, Neural Networks, etc.); experience with forecasting and time series modeling is a plus
• 3+ years of experience with various types of data repositories (e.g., data warehouses, data lakes, data marts), metadata management, dimensional modeling, and/or ETL / integration; experience with Snowflake and other cloud repositories are a plus
• Proven ability to deliver analyses iteratively (i.e., before they are "perfect" and finished), and use said analyses to build trust and grow demand for further work
• Proven ability to independently present to stakeholders and adjust communication style depending on the audience (e.g., knowing how deeply to describe the Client techniques utilized by
• Proficiency in R, Python, Spark (pySpark, Spark Scala), or related languages for the application of data analyses and machine learning – we are a Python shop and Python/pySpark is a plus
• Proficiency in one of more dialects of SQL and ability to optimize queries
• Proficiency in one or more visualization tools (e.g., Tableau, PowerBI, Looker, etc.); experience with developing point-and-click interfaces (e.g., plot.ly Dash, Streamlit, R Shiny, JavaScript) is a plus

Nice To Have Experience

• Experience with DevOps practices, including the use of git repositories
• Experience analyzing real estate portfolio assets, financial statements, or other types of complexly hierarchical, "wide" data that is difficult to interpret without consulting subject matter experts
• Experience in Financial Services, Hedge Funds, Private Equity, and/or Real Estate – the more of these you have, the better, but we also appreciate the perspective of data scientists from other fields if you can make the case that your experience is relevant to solving our problems
• Experience with working on a cloud platform and the use of distributed tools; use of the Microsoft Azure platform (e.g., Azure-SQL, Azure Databricks, Azure Machine Learning, Data Factory, Data Lake)