Data Parser

Quantitative analysis plays a key role in our process and the right candidate will partner with the firm’s investment staff, data scientist, advisors in predictive analytics and economics as well as the firm’s real estate operators to deliver breakthrough analysis to support a winning strategy in a dynamic investment environment. The intersection of quantitative and investment analysis is ripe for those interested in charting a new course for real estate investment management and this high-impact role provides the opportunity to see efforts translate to action. The right candidate will gain exposure to all facets of the investment process working directly with key decision makers to develop tangible data-driven models which seek to generate alpha through operational efficiencies or arbitrage opportunities. Development of predictive and analytics methods and models to identify opportunities and inefficiencies that drive outperformance in real estate.

• Ownership of all stages of the data science life cycle from curating data (internal, external, and alternative) and exploration therein to validation/testing exercises and delivery of analytical solutions, visualization, and/or tools
• Write and document efficient, modular, and dependable scripts for varying workflow processes
• Ongoing maintenance (refinement) and performance monitoring post implementation of models
• Ability to codify high-impact solutions from ambiguous starting conditions
• Ad-Hoc research projects that will range widely in scope and focus

Qualifications:

• Suggested Qualifications: Engineering, Computer Science, Mathematics and/or Physics (PhD/M.S. in a technical field is an advantage
• > > Preference towards computational-based/quantitative backgrounds
• At least 3+ years of experience in a data science/analytical position spanning applied science problems up to big data problems (all areas of focus considered)
• > > Extensive experience developing algorithms and production-grade code (peer reviewed extensively and/or implemented on real systems)
• > > Experience in automating processes in order to gain efficiencies
• > > Education or working experience across statistical frameworks (Monte Carlo simulations, Optimization, Modeling & Simulation, and/or Algorithm development)
• Proficiency in computer programming languages: Matlab, Python, Perl, R, C/C++ or any other similar frameworks for solving computational problems
• Demonstrated workflow and time management skills capable of advancing multiple projects with varying timelines
• Ability to work across non-standardized or standardized data-sets
• > > Ranging from numerical data to images to natural language/text inputs
• > > Ability to source & clean data across numerous files & data types (e.g. extracting from PDFs or images for text or parsing data files with specific machine formats/character encodings or web-scraping data via JSON or web APIs)
• Highly developed research, communication, analytical and problem-solving skills
• Demonstrated ability to stay current with new business applications, technical skills, and research
• Self-starter who can work well within a team or independently

Preferred (but not required):

• Experience working in R&D / Prototyping up to Production-level systems to deploy analytical solutions for specific problem sets
• > > Exposure with low to high fidelity modeling (applied computational science/mathematic to real systems or software)
• General academic knowledge or working experience across computer vision, machine learning (deep learning), and/or alternative analytical methods
• Familiarity with working across databases (SQL/NoSQL, Hadoop, Spark)
• General knowledge about real estate data (data vendors, structured sources) and/or alternative data sources
• Experience with cloud infrastructures

Job Type: Full-time