Sr Pncpl Data Scientist

Overview

03-Feb-2026

US Remote

10685

As the recognized global standard for project-based businesses, Deltek delivers software and information solutions to help organizations achieve their purpose. Our market leadership stems from the work of our diverse employees who are united by a passion for learning, growing and making a difference. At Deltek, we take immense pride in creating a balanced, values-driven environment, where every employee feels included and empowered to do their best work.

Our employees put our core values into action daily, creating a one-of-a-kind culture that has been recognized globally. Thanks to our incredible team, Deltek has been named one of America s Best Midsize Employers by Forbes, a Best Place to Work by Glassdoor, a Top Workplace by The Washington Post and a Best Place to Work in Asia by World HRD Congress.

We re seeking a Senior Principal Data Scientist to provide business and technical leadership for Deltek s newly established Enterprise Data Science team. Reporting to the Director of Data Science, you ll define how we build, deploy, and scale machine learning capabilities on our Snowflake intelligent data platform to enable business decision-making priorities.

This position requires someone who combines deep machine learning expertise with strong architectural thinking and the ability to establish technical standards that will guide our data science practice as it grows. You ll work on the hardest technical problems while mentoring senior engineers and ensuring our ML systems are built for production scale, reliability, and maintainability.

This is an opportunity to architect a data science function from the ground up at an established enterprise software company.

Advanced Model Development

• Lead development of complex, high-impact models for customer health scoring, churn prediction, revenue optimization, and other key business-critical use cases
• Tackle technical challenges that require deep expertise: class imbalance, temporal dependencies, multi-objective optimization
• Design experimentation frameworks for A/B testing and causal inference
• Ensure models are explainable, fair, and aligned with business constraints

Mentorship & Knowledge Sharing

• Mentor senior data scientists on technical approaches, code quality, and ML best practices
• Conduct design reviews and code reviews to maintain high technical standards
• Facilitate knowledge transfer sessions on advanced techniques and architectural patterns
• Build internal documentation and playbooks that codify team practices
• Help team members grow their technical skills and advance their careers

Cross-Functional Collaboration

• Translate business requirements into technical architecture and feasibility assessments
• Work with data engineering leadership to ensure platform capabilities support ML workloads
• Collaborate with the AI Center of Excellence on integration opportunities and enterprise AI strategy
• Communicate technical decisions, trade-offs, and recommendations to leadership and stakeholders
• Represent data science technical perspective in cross-functional planning and architecture discussions

US Citizenship is required for this position.

• Ph.D. in Data Science, Statistics, Computer Science, Machine Learning, or related quantitative field (or Master s with 4+ years relevant experience)
• Extensive hands-on experience building and deploying production ML systems at scale
• Deep expertise in supervised and unsupervised learning
• Experience designing MLOps architectures: feature stores, model monitoring, automated retraining
• Track record of making sound technical decisions that balance multiple constraints (performance, maintainability, time-to-market)
• Understanding of cloud data platforms and modern data architectures

• Proven ability to provide technical leadership without requiring people management authority
• Strong mentorship skills with experience developing other data scientists
• Excellent communication skills to explain complex technical concepts and architectural decisions to diverse audiences
• Strategic thinking to anticipate technical challenges and design systems that scale
• Collaborative approach to working across teams and building consensus on technical direction
• Self-directed with ability to identify high-impact problems and drive solutions independently

• Snowflake experience and deep understanding of cloud data warehouse architectures
• Experience with B2B SaaS analytics, customer health scoring, or churn prediction at scale
• Familiarity with dbt and modern data transformation patterns
• Knowledge of dimensional modeling and enterprise data warehouse concepts
• Deep learning expertise for future applications
• Background in causal inference, experimentation design, or Bayesian methods
• Container orchestration (Docker, Kubernetes) for model deployment
• Experience building data science capabilities or teams from scratch
• Experience with time series forecasting or survival…