Lead Data Scientist

Compass; Seattle (WA); On-site; USD 150,000 - 210,000; Full time

Job summary

Compass in Seattle seeks a Lead Data Scientist to drive advanced analytics, ML models, and data-driven decision making across the organization. You will architect scalable solutions, guide strategy, and partner with engineering and business leaders to translate goals into actionable insights.

You will lead end-to-end model development, validate rigor, and productionize solutions while mentoring junior data scientists and promoting best practices in MLOps and software engineering.

Qualifications

• 5+ years of experience leading end-to-end data science projects.

Responsibilities

• Lead end-to-end development, validation, and deployment of large-scale predictive models.

Skills

Time-series forecasting

Deep learning

Causal inference

Software engineering

Business acumen

Cross-functional leadership

Mentoring

Communication

Education

Master’s degree in Computer Science/Statistics/Economics/Mathematics

PhD preferred

Tools

Python

SQL

MLOps

Cloud platforms

Job description

• We are seeking a highly skilled and motivated Lead Data Scientist to join our data science team
• In this role, you will leverage your deep expertise in machine learning, statistical modeling, and data analysis to solve our most complex problems
• You will set the standard for data science excellence, architect scalable solutions, and help define the long-term analytical strategy
• You will partner with senior business stakeholders and engineering leaders to uncover insights, develop cutting-edge data-driven solutions, and drive initiatives that directly shape company-wide strategic planning, resource allocation, and product innovation
• Lead the end-to-end development, validation, and deployment of large-scale predictive models and algorithms that inform strategic business decisions and market trend analysis
• Design and execute rigorous data-driven research to analyze the impact of multi-faceted factors on business outcomes, tackling the organization’s most highly ambiguous and open-ended problems
• Collaborate deeply with senior business stakeholders and engineering partners to identify strategic opportunities, translate overarching business goals into complex analytical frameworks, and deliver high-impact actionable insights
• Synthesize and communicate highly complex methodologies, technical trade-offs, and strategic findings clearly to both C-level executives and technical audiences
• Act as a technical mentor to other data scientists, fostering a culture of continuous learning, rigorous peer review, and adherence to state-of-the-art methodologies

Requirements

• Deep expertise in key data science domains (e.g., time-series forecasting, deep learning, causal inference)
• Strong advocate for clean code principles, software engineering best practices, and technical standards
• Strong business acumen and strategic thinking, with a proven ability to understand the broader business context, evaluate tradeoffs, and align analytical projects with organizational goals
• Proven experience leading complex, cross-functional projects and applying advanced methodologies to solve ambiguous business problems
• 5+ years of experience in data science with a proven track record of conceptualizing, leading, and delivering highly successful, end-to-end data science projects
• Exceptional communication and collaboration skills, with a proven ability to work effectively in a fast-paced, cross-functional environment
• Experience mentoring and guiding junior team members, overseeing project quality, and investigating root causes of complex technical challenges
• Master’s degree or PhD in Computer Science, Statistics, Economics, Mathematics, or a related quantitative field
• Hands-on experience productionizing machine learning models and strong familiarity with MLOps concepts and workflows
• Demonstrated proficiency in Python and SQL for complex data manipulation, statistical analysis, and model development
• Extensive practical experience architecting solutions using a broad range of methodologies (e.g., prediction, segmentation, NLP)
• Experience in the Real Estate industry or other market-driven domains is a plus