Data Scientist

Job not on LinkedIn

🔥 12 hours ago

🇺🇸 United States – Remote

💵 $155k - $175k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

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Pearl

WebsiteLinkedInAll Job Openings

1 - 10 employees

🤝 B2B

👥 HR Tech

🎯 Recruiter

B2B • HR Tech • Recruitment

Pearl is a company that provides tools for overqualified and overlooked jobseekers, helping them enhance their visibility to potential employers. Their main offering is a portfolio builder that allows digital professionals to create visually appealing and trackable portfolios. By emphasizing the importance of personalized portfolios over traditional resumes, Pearl aims to improve job seekers' chances of landing opportunities that align with their skills and aspirations, partnering with hiring teams to facilitate these connections.

📋 Description

• Lead advanced research and predictive modeling focused on residential housing and energy performance data • Manage research with external consultants and statistical firms to identify correlations and causal relationships between home performance and housing-related data • Apply regression analysis, propensity score matching, and instrumental variable methods where appropriate • Analyze approximately 92 million residential SCOREs and energy models to identify inaccurate outputs • Use anomaly detection, outlier analysis, and field-collected home-characteristics data for validation • Analyze modeled energy consumption, physical home characteristics, and utility billing data to improve energy-model accuracy • Analyze relationships between field-collected performance characteristics and SCORE outputs to improve SCORE accuracy • Support development of new performance metrics, such as Total Cost of Ownership • Evaluate integration of climate-risk data into the SCORE and analyze relationships between resilience features and extreme-climate-event outcomes • Serve as primary technical point of contact for external data and statistical partners • Assist with 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 applied experience in statistical analysis and predictive modeling • Experience involving large, real-world (non-experimental) datasets • Hands-on experience with causal inference methods, including regression analysis, propensity score matching, and instrumental variable approaches • Understanding of when correlation-based methods are and are not sufficient to support causal claims • Experience with anomaly detection and outlier analysis techniques applied to large datasets • Strong proficiency in Python or R and SQL • Experience validating model outputs against ground-truth or field-collected data • Ability to translate statistical findings into clear, non-technical explanations • Experience working directly with external consultants, research firms, or academic partners • Experience with feature importance analysis and model interpretability techniques preferred • Familiarity with housing, real estate, energy, or utility data preferred • Experience integrating or evaluating climate/environmental risk data into predictive models preferred • Track record of authoring or co-authoring published research preferred • Experience working with ambiguity and scale preferred • Comfortable working semi-independently, with support and partnerships 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 employee • FSA, HSA, and dependent care accounts • Life insurance coverage • Employer-paid cell phone service • 401(k) with employer match up to 4% • Stock options • 15 vacation days during the calendar year • Paid holidays, including the week between Christmas and New Year's Day • Floating holiday for your birthday • Sick days • Paid parental leave • Flexible work environment • Broad responsibilities with high autonomy • Supportive, collaborative environment • Equal opportunity workplace • Candidates from all backgrounds and life experiences encouraged to apply