Lead Data Scientist

Lead Data Scientist
American Public Education, Inc.

The Lead Data Scientist is a crucial team member within American Public Education, Inc’s (APEI) enterprise Data & Analytics team. This role is pivotal for the company’s growth journey with advanced analytics, including machine learning as well as GenAI. It is a senior individual contributor but that doesn’t diminish the technical influence, stakeholder influence, and overall strategic importance of the role. Join us on this journey and our broader mission of powering purpose, potential and prosperity for those in service to others!

As a Lead Data Scientist, you’ll be responsible for applying innovative statistical and machine learning methods in a scientifically rigorous manner to dive into the largest and most complex data across the enterprise to answer the most difficult questions that are foundational to driving real-world value by offering deep insight into every aspect of the business.

You will be responsible for defining technical data science strategy, establishing data science standards, and guiding multi-team initiatives that advance organizational analytics and business insights, data science and ML delivery of scalable solutions, and building new organizational capabilities with broader GenAI capabilities. The role is highly consultative in nature. You also will influence senior business leaders and stakeholders, product, and technology leaders to adopt data‑driven approaches to solving complex business problems, improve business strategy and growth opportunities, as well as increasing efficiency of tactical business operations.

Given the enterprise level nature of this role there is strong opportunity for impact across all value streams throughout the business. Determining and prioritizing the best opportunities for business value is done in partnership with data & analytics product leadership and business stakeholders.

The Lead Data Scientist is responsible for establishing modeling and experimentation guardrails. You will have significant technical influence and will mentor junior and senior individual contributors within the team. You will also put in place machine learning ops solutions that help accelerate delivery across the organization and ensure solutions are safe, scalable, and sustainable.

The Lead Data Scientist had no direct reports but does coach less experienced peer team members.

Responsibilities: 

• 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