Staff Data Scientist

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

📋 Description

• Design and implement high-quality statistical and machine learning systems for production.

• Collaborate directly with the CTO to create innovative analytical methodologies.

• Convert research concepts into scalable software for production use.

• Develop robust evaluation frameworks and consistently enhance model performance.

• Enhance the reliability, maintainability, and engineering quality of the machine learning platform.

• Work closely with software engineering teams to deploy new analytical capabilities into production.

• Set technical standards and establish best practices for Data Science engineering.

• Engage in recruiting, mentoring, and shaping the future of the Data Science team.

• Create methodologies for residential valuations.

• Enhance the precision and resilience of Kelley Blue Book Home Valuations.

• Measure confidence and uncertainty in valuation models.

• Develop interpretable machine learning systems aimed at consumers and professional appraisers.

• Create methodologies tailored for rare and atypical properties.

• Transform analytical concepts into production systems utilized nationwide.

⛳️ Requirements

• Solid foundation in machine learning and statistics.

• Proven experience in developing production-quality machine learning systems.

• Proficient in Python programming.

• Strong software engineering principles, including testing, version control, modular design, and the ability to write maintainable production code.

• Capable of reasoning from fundamental principles and navigating through ambiguity.

• Skilled at devising solutions for complex statistical and engineering problems.

• Proficient in articulating complex technical concepts clearly.

• Enjoys collaborative problem-solving environments.

• Comfortable providing and receiving constructive technical feedback.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health and wellness benefits.

• Opportunities for professional development and continuous learning.

• Flexible working hours and remote work options.

• Collaborative and innovative work environment.