Sr Principal Data Scientist

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

This is a senior technical leadership role focused on shaping the future of applied machine learning and agentic AI systems at scale. You will define how advanced ML models and AI sub-agents are designed, evaluated, and deployed across the customer lifecycle to drive growth, retention, and monetization. The role operates at the intersection of architecture, hands-on modeling, and strategic influence, requiring the ability to move seamlessly from prototype to production. You will work with large-scale, high-dimensional datasets capturing real-world workflows and decision patterns over many years. Partnering closely with product and engineering leadership, you will help define technical standards, system design principles, and long-term AI strategy. This role also carries strong organizational impact, mentoring senior data scientists and raising the bar for modeling rigor and production excellence.

• Define and lead the technical direction for applied ML and agentic AI systems across the customer lifecycle, including growth, retention, and monetization use cases.
• Architect scalable AI sub-agent systems, including reasoning frameworks, tool use, evaluation methods, guardrails, and production safety mechanisms.
• Establish organization-wide standards for modeling, experimentation, and evaluation, including offline metrics, online testing, and production monitoring.
• Design and deliver high-impact machine learning models and AI systems that directly influence product and business outcomes.
• Drive decisions around data foundations, feature engineering, and knowledge layers while ensuring privacy, governance, and trust.
• Partner with senior leaders across product and engineering to shape roadmap priorities and long-term AI strategy.
• Mentor and guide staff and principal-level data scientists, improving technical rigor, design quality, and execution across the team.

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.