Staff Data Scientist

Jobgether; United States; On-site; USD 225,000 - 250,000; Full time

Job summary

Jobgether partners with a client seeking a Staff Data Scientist in the United States to design and deploy production-grade ML systems for residential property valuation. You will work with executive leadership to craft new valuation methodologies and scalable software, focusing on interpretable models, robust evaluation, and uncertainty quantification.

You will mentor team members and help shape technical standards and the long-term direction of the Data Science organization, while delivering

Qualifications

• Strong background in machine learning and statistics applied to real problems.
• Experience deploying production-quality ML systems, not only research.
• Excellent Python and software engineering fundamentals.
• Experience with testing, version control, and maintainable code.
• Ability to design interpretable models with robust evaluation.
• Willingness to mentor teammates and set technical standards.

Responsibilities

• Design, develop, and implement production-quality ML systems for property valuation.
• Collaborate with leadership to create innovative valuation methodologies.
• Translate research ideas into scalable, production-ready software.
• Create rigorous evaluation frameworks for model performance and reliability.
• Develop methods for uncertainty estimation and rare-property use cases.
• Build interpretable ML systems with transparent results for users.
• Work with software engineers to integrate analytical capabilities into production.
• Improve reliability, testing, and engineering quality of the ML platform.
• Contribute to internal technical standards and hiring in Data Science.
• Help shape long-term direction for the growing DS org.

Skills

Python programming

Production ML systems

Statistics

Interpretable ML

Model evaluation

Mentoring

Tools

Git

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Data Scientist based in United States.

This is a high-impact opportunity for a senior data science professional to help shape the future of statistical modeling and machine learning in residential real estate valuation.

You will work closely with executive technical leadership to solve complex, open-ended statistical and engineering problems.

The role combines hands-on development with the creation of new valuation methodologies and production-grade analytical systems.

Your work will directly support products and platforms used by consumers, financial stakeholders, and professional appraisers across the United States.

The focus is on interpretable machine learning, statistical modeling, optimization, uncertainty estimation, and reliable production systems rather than deep learning or LLM research.

As the Data Science organization grows, you will also help establish technical standards, mentor future team members, and influence its long-term direction.

This role is ideal for a technically strong, curious problem solver who enjoys turning novel analytical ideas into trusted software.

Accountabilities

• Design, develop, and implement production-quality statistical and machine learning systems for residential property valuation and related analytical applications.
• Partner directly with technical leadership to develop innovative valuation methodologies and solve challenging statistical problems that may not have established solutions.
• Translate research concepts and analytical ideas into scalable, maintainable, production-ready software.
• Design rigorous evaluation frameworks to measure model performance, reliability, accuracy, and robustness, and continuously improve analytical outcomes.
• Develop methodologies for complex use cases, including rare and atypical properties, confidence estimation, and uncertainty quantification.
• Build interpretable machine learning systems that provide transparent and defensible results for consumers and professional users.
• Collaborate closely with software engineering teams to integrate new analytical capabilities into production systems.
• Improve the reliability, maintainability, testing, and overall engineering quality of the machine learning platform.
• Establish technical standards, modeling practices, and engineering best practices for the Data Science function.
• Contribute to technical hiring, mentoring, knowledge sharing, and the development of future Data Science team members.
• Help shape the long-term technical direction and capabilities of the growing Data Science organization.

Requirements

• Strong professional background in machine learning and statistics, with experience applying advanced analytical techniques to complex business or technical problems.
• Demonstrated experience building and deploying production-quality machine learning systems rather than working exclusively in research or experimental environments.
• Excellent Python programming skills and strong software engineering fundamentals.
• Experience with testing, version control, modular architecture, maintainable code, and other practices required for reliable production software.
• Strong understanding of statistical modeling, interpretable machine learning, optimization, and rigorous model evaluation.
• Ability to reason from first principles and solve ambiguous, open-ended problems where established methodologies may not exist.
• Strong analytical and problem-solving skills, with an ability to develop elegant and defensible solutions to difficult statistical and engineering challenges.
• Excellent communication skills, including the ability to explain complex technical concepts clearly to both technical and non-technical stakeholders.
• Collaborative approach to solving challenging technical problems, with the ability to give and receive constructive technical feedback.
• Ability and interest in mentoring colleagues, contributing to technical standards, and helping shape a growing Data Science organization.
• A senior or staff-level mindset, with the technical depth and ownership required to influence modeling, engineering, and organizational direction.

Benefits

• Compensation range of $225,000–$250,000 per year.
• Opportunity to work on high-impact statistical and machine learning systems used in residential real estate valuation.
• Direct collaboration with senior technical leadership on challenging and open-ended analytical problems.
• Hands-on ownership of production machine learning systems and next-generation valuation methodologies.
• Opportunity to influence technical standards, engineering practices, hiring, and the long-term direction of a growing Data Science organization.
• Significant potential for increased technical leadership responsibilities as the team expands.
• Opportunity to work on interpretable and explainable machine learning systems where accuracy, transparency, and defensibility are critical.