The Principal Data Scientist role at SRS Distribution is looking to drive the design, development, and deployment of scalable AI, ML, and data science solutions to support complex business systems.
Requirements
- Mastery of a wide variety of machine learning models and AI techniques, including MLOps best practices
- Experience with regulatory and ethical implications of AI/ML in production environments
- Familiarity with Microsoft AI-900 certification, TensorFlow Developer Certificate
- Deep expertise in AI/ML modeling and MLOps
- Strategic and technical leadership across enterprise-level initiatives
- Excellent problem-solving and critical thinking abilities
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
Other
- 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
- Strong communication and influence at the executive level
- Occasional travel (<10%) may be required for strategic planning, leadership meetings, or cross-functional alignment
- Minimum Years of Work Experience: 10+ years of experience in data science, machine learning, or AI, with increasing technical leadership responsibilities
- Preferred Qualifications: Proven leadership in DS/AI/ML/Optimization within complex enterprise ecosystems
