Lead Data Scientist

Role Overview

• Define the details of and execute the data science technical strategy, aligned to business objectives and overall data/analytics senior leadership vision and strategy.
• Collaborate on the data science roadmap with data & analytics product management and stakeholders.
• Mentor peer team members for effective delivery as well as to help build a high-performing data science and consultative business insights team.
• Provide cross team technical reviews, thought partnership, and coaching.
• Deliver effective and sustainable ML and GenAI products that drive measurable business value.
• Lead cross domain programs that create reusable platforms, shared modeling components, and standardized evaluation frameworks.
• Establish technical guardrails for modeling, feature engineering, experimentation, and MLOps across teams.
• Design scalable ML/GenAI systems and reference designs, balancing performance, latency, cost, and compliance.
• Review and approve models, ensuring rigor in causal inference, statistical methods, monitoring, and evaluation.
• Introduce new methods and technologies when needed to unlock value or resolve domain‑level challenges.
• Guide teams in designing robust experiments to measure outcomes and value.
• Plan work and help with managing team capacity with data product owners/management.
• Define MLOps strategy, including feature stores, observability, drift/performance monitoring, retraining policies, and rollback protocols.
• Partner with engineering and platform teams to select tools, build roadmaps, and set SLAs for data quality, reliability, and model governance.
• Ensure compliance with privacy, security, and Responsible AI requirements.
• Establish ML platform governance for performance, cost optimization, and security compliance.
• Partner with data platform team and solutions architects to solve data gaps or optimize data pipelines for advanced analytics.
• Interacts, consults with and influences senior management at various levels of the organization, with various internal organizations (e.g. management, finance, marketing, academics, operations, legal).
• Acts as liaison between the business operations and available data, working on various initiatives to maintain visibility and understanding of the data and decisions being made.
• Promotes identification of best practices and fosters cross functional sharing of initiatives, innovation and best practices.
• Performs other duties as assigned.

Requirements

• 8+ years of experience in data science and machine learning with repeated large scale impact and increasing responsibility
• 2+ years of experience leading development of AI/ML data products and systems
• Bachelor of Science in Analytics, Computer Science, Mathematics, or equivalent with Masters in Data Science or related degree highly preferred
• Deep expertise in machine learning and ML frameworks, applied mathematics, and statistics
• Proven track record leading multi team initiatives, platform efforts, or domain level AI/ML strategies
• Proven ability to evaluate models and systems for accuracy, fairness, scalability, and business value
• Experience with MLOps
• Experience optimizing lead funnel, developing forecasting models, and student retention optimization in the context of higher education is highly preferred
• Experience with Agentic AI system design
• Deep expertise in SQL and Python as well as ELT patterns and tooling
• Strong expertise in data visualization to convey information effectively
• Deep mastery of experimentation design and execution including A/B testing
• Proven experience with cloud data and analytics platforms with Snowflake, Power BI, and Azure highly preferred
• Strong problem solving and analytical skills alongside creative thinking and innovative approaches within a strategic and broad perspective
• Broad conceptual judgment, initiative, and must possess theoretical thinking skills.
• Track record of delivering large-scale, mission-critical AI/ML systems with measurable business impact
• Exceptional stakeholder management and influence across business and technology
• Excellent verbal and written communication skills, ability to communicate and influence effectively with all levels of the organization from analysts to C-Level executives.

Tech Stack

• Azure
• Cloud
• Python
• SQL

Benefits

• Competitive salary
• Flexible working hours
• Professional development budget
• Home office setup allowance
• Global team events