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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in hierarchical forecasting, time series analysis, and econometric methods, with a strong focus on the housing market and its economic drivers. Proficient in deploying machine learning models and communicating insights to stakeholders.
Highest-signal resume keywords
Hierarchical ForecastingTime Series AnalysisEconometric MethodsMachine Learning TechniquesCloud-Based Platforms
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data CleaningFeature EngineeringModel EvaluationCross-ValidationBacktestingForecasting Accuracy MetricsLarge-Scale DatasetsAI Agent DevelopmentStress-Testing FrameworkIndependent Research
Soft Skills
Excellent Communication Skills
Tools & Technologies
Distributed Computing FrameworksSparkCloud-Based Tools
Certifications & Qualifications
Master’s DegreePhD Degree
Industry Keywords
Housing MarketEconomic FactorsDemographic DriversForecast ProductionScenario Models
Tech Stack
Tools & technologiesCloudSpark
About the role
Key responsibilities & impact- Develop hierarchical forecasts for the housing market at various regional levels
- Identify economic and demographic drivers of housing market growth across regions
- Extract features that predict housing market trends 1 to 2 years in the future
- Collaborate with engineering to deploy models into production environments
- Contribute to monthly forecast production
- Communicate forecast performance and housing market outlook to business partners and senior leadership
- Develop scenario models covering a wide range of housing market outcomes
- Contribute to a company-wide stress-testing framework
- Conduct independent research and apply research methods to real-world problems
Requirements
What you’ll need- Strong interest and understanding of the housing market and influencing economic factors
- Experience with time series, panel data, and hierarchical forecasting
- Strong foundation in traditional econometric methods and modern machine learning techniques
- Proficiency in data cleaning, preprocessing, and feature engineering for time series data
- Experience with large-scale datasets
- Familiarity with distributed computing frameworks such as Spark
- Ability to design and implement model evaluation and validation strategies, including cross-validation and backtesting
- Experience with time series forecasting accuracy and performance metrics
- Proficiency in cloud-based platforms and tools for deploying and monitoring machine learning models
- Proficiency in building AI agents to automate manual work
- Excellent verbal and written communication skills
- 2+ years of proven experience working in time series/spatial forecasting
- Master’s or PhD degree in Mathematics, Statistics, Economics, Econometrics, Physics, Earth Sciences, or a related scientific field
Benefits
Comp & perks- Equity awards based on experience, performance, and location
- Remote work from a physical location of choice
- Flexible work from wherever employees are most productive
- Equal employment opportunity and inclusive work environment
- Disability or special-need accommodation