Sr Principal Data Scientist

Requirements:

• 12 plus years of experience in applied data science or machine learning, or 14 plus years of total experience, with an advanced degree in a quantitative field preferred.
• Proven track record of leading end-to-end ML initiatives from concept to production with measurable business impact.
• Deep expertise in machine learning techniques including gradient boosting, linear models, deep learning, transformer architectures, embeddings, and contextual bandits.
• Strong understanding of agentic AI systems, including multi-step reasoning, retrieval-augmented generation, tool use, and evaluation frameworks.
• Solid background in causal inference, experimentation design, and statistical methods such as A/B testing, uplift modeling, and quasi-experimental techniques.
• Experience operating large-scale ML systems in production, including pipelines, monitoring, drift detection, and retraining strategies.
• Proficiency in Python and SQL, with experience using ML and data platforms such as Spark, Databricks, Snowflake, PyTorch, or similar tools.
• Strong business understanding of SaaS metrics such as churn, retention, expansion, ARR, and cohort analysis.
• Demonstrated ability to influence senior stakeholders and mentor advanced technical talent in complex organizational environments.
• Strong ability to operate in ambiguous environments, define problems independently, and drive alignment across teams.

Benefits:

• Competitive compensation aligned with senior principal-level responsibilities.
• Performance-based incentives tied to impact and delivery outcomes.
• Flexible work arrangements, including remote and hybrid options.
• Comprehensive health, wellness, and employee assistance programs.
• Learning and development support for continuous professional growth.
• Opportunity to work on large-scale AI systems with significant real-world impact.
• Inclusive and collaborative work culture supporting innovation and autonomy.