Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Spearhead sophisticated research and predictive modeling centered on residential housing and energy performance data

• Oversee research initiatives with external consultants and statistical firms to uncover correlations and causal relationships between home performance and housing-related data

• Implement regression analysis, propensity score matching, and instrumental variable methods as suitable

• Examine approximately 92 million residential SCOREs and energy models to pinpoint inaccurate outputs

• Employ anomaly detection, outlier analysis, and field-collected home-characteristics data for validation purposes

• Assess modeled energy consumption, physical home attributes, and utility billing data to enhance energy-model precision

• Investigate connections between field-collected performance characteristics and SCORE outputs to refine SCORE accuracy

• Assist in the creation of new performance metrics, such as Total Cost of Ownership

• Analyze the incorporation of climate-risk data into the SCORE and evaluate the relationships between resilience features and extreme-climate-event outcomes

• Act as the main technical liaison for external data and statistical partners

• Contribute to the authorship of white papers, briefs, and publications for Pearl's research page and academic journals

⛳️ Requirements

• Master's degree in Statistics, Economics, Data Science, Applied Mathematics, or a related quantitative field (or equivalent experience)

• 4+ years of practical experience in statistical analysis and predictive modeling

• Experience with large, real-world (non-experimental) datasets

• Proficient in causal inference methods, including regression analysis, propensity score matching, and instrumental variable approaches

• Knowledge of the appropriate contexts for correlation-based methods and their limitations in supporting causal claims

• Experience with anomaly detection and outlier analysis techniques applied to extensive datasets

• Strong skills in Python or R and SQL

• Proven experience validating model outputs against ground-truth or field-collected data

• Ability to articulate statistical findings into clear, non-technical explanations

• Familiarity with working directly with external consultants, research firms, or academic collaborators

• Preferred experience with feature importance analysis and model interpretability techniques

• Background in housing, real estate, energy, or utility data is preferred

• Experience in integrating or assessing climate/environmental risk data within predictive models is preferred

• A record of authoring or co-authoring published research is preferred

• Comfort with ambiguity and scale is preferred

• Ability to work semi-independently, with support and collaboration is preferred

🏝️ Benefits

• 100% remote work environment

• Medical, vision, and dental coverage provided at no cost for employees and their families

• Option to purchase upgraded medical, vision, and dental coverage at minimal cost to employees

• FSA, HSA, and dependent care accounts available

• Life insurance coverage included

• Employer-paid cell phone service

• 401(k) plan with employer match up to 4%

• Stock options offered

• 15 vacation days per calendar year

• Paid holidays, including the week between Christmas and New Year's Day

• Floating holiday for your birthday

• Sick days available

• Paid parental leave

• Flexible work environment

• Broad responsibilities coupled with high autonomy

• Supportive, collaborative workplace culture

• Equal opportunity employer

• Candidates from all backgrounds and life experiences are encouraged to apply