Principal Data Scientist

The Principal Data Scientist is a senior expert and thought leader responsible for driving the design, development, and deployment of scalable AI, ML, and data science solutions to support complex business systems. This role champions technical excellence in MLOps, provides strategic leadership in AI/ML architecture, and partners closely with both technical and business stakeholders to influence outcomes across the enterprise. The ideal candidate combines deep technical expertise with strong executive communication skills and a proven record of delivering measurable business impact.

Key Responsibilities:

• Drive the design and development of advanced AI/DS/ML solutions that support large-scale and complex business operations
• Lead technical excellence in MLOps practices, ensuring scalable and reliable machine learning deployments
• Serve as a thought leader in AI/ML, mentoring junior data scientists and guiding architectural decisions and long-term roadmaps
• Own cross-functional collaboration efforts with engineering, data engineering, platform, and product teams to ensure seamless delivery and adoption of AI/ML products
• Partner with business and functional leaders to align AI/DS strategy with organizational goals and influence decision-making through data-driven insights
• Represent the data science function in strategic discussions and executive forums

Direct Manager/Direct Reports:

• Direct manager: Sr. Director of Applied AI
• Direct reports: No direct reports but may serve as a team lead or player-coach, providing mentorship to senior data scientists and technical contributors

Travel Requirements:

• Occasional travel (<10%) may be required for strategic planning, leadership meetings, or cross-functional alignment
   

Physical Requirements:

• Standard office-based physical requirements including prolonged computer usage and participation in virtual and in-person meetings
   

Working Conditions:

• Hybrid work environment with a combination of remote and on-site work at 7440 S. Hwy 121, McKinney, TX 75070

Minimum Qualifications:

• Master’s degree or PhD in a quantitative field (e.g., Statistics, Machine Learning, Applied Mathematics), or at least 10 years of professional experience with a strong track record of building and deploying scalable AI/ML systems
• Mastery of a wide variety of machine learning models and AI techniques, including MLOps best practices
• Demonstrated ability to translate complex AI/ML concepts into strategic business impact
• Experience leading cross-functional initiatives and delivering data products at enterprise scale
• Strong communication and influence at the executive level
   

Preferred Qualifications:

•  Proven leadership in DS/AI/ML/Optimization within complex enterprise ecosystems
• Experience managing high-performing data science teams and leading large-scale, cross-functional programs
• Familiarity with regulatory and ethical implications of AI/ML in production environments
• Demonstrated success in aligning AI initiatives with key business KPIs and influencing strategic priorities
   

Minimum Education:

•  Master’s degree in a relevant quantitative field or equivalent practical experience
   

Preferred Education:

• PhD in Machine Learning, Statistics, Applied Mathematics, or a related discipline

Minimum Years of Work Experience:

• 10+ years of experience in data science, machine learning, or AI, with increasing technical leadership responsibilities
   

Certifications:

• Not required, but relevant certifications (e.g., Microsoft AI-900 certification, TensorFlow Developer Certificate) are a plus.

Competencies:

• Deep expertise in AI/ML modeling and MLOps
• Strategic and technical leadership across enterprise-level initiatives
• Excellent problem-solving and critical thinking abilities
• Strong cross-functional collaboration skills
• Outstanding executive communication and stakeholder management
• High level of initiative, innovation, and long-term strategic thinking
   

Work Location:

• Hybrid – 7440 S. Hwy 121, McKinney, TX 75070

      

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