• Apply statistical analysis, data mining, and machine learning techniques to address operational needs • Develop, validate, and deploy predictive, descriptive, and diagnostic models in support of program objectives • Perform exploratory data analysis (EDA) to identify trends, patterns, anomalies, and risk indicators • Collaborate with data engineering teams to define data requirements, feature engineering approaches, and analytic pipelines • Ensure analytical methods and outputs are explainable, reproducible, and auditable • Develop and document model assumptions, methodologies, limitations, and performance metrics • Support use cases such as forecasting, risk scoring, anomaly detection, classification, and segmentation • Create visualizations, dashboards, and analytical summaries to communicate findings to stakeholders • Support validation, testing, and continuous monitoring of models to ensure ongoing performance and compliance • Produce high-quality documentation, technical memos, and briefings in accordance with federal standards • Participate in Agile/Hybrid delivery processes, including sprint planning, reviews, and status reporting

• Own all things data at Philo: ensure that stakeholders at Philo have access to the timely and accurate data driven insights that they need to do their jobs. • Oversee the core data science work executed in cross-functional teams to drive product goals, including product experiments and A/B tests, Growth & Acquisition modeling, and product insights, including customer journey analysis and measuring effectiveness of content search and recommendation systems. • Own the quality and performance of the data platform at Philo, including platform architecture and instrumentation, data collection/processing/validation, data governance, and security and compliance. • Ensure that we are collecting the right data and events, processing them in a scalable and modular way, and building a foundation of reliable data that teams across the company can build insights from. • Collaborate closely with the engineering team and AI/ML engineers to support the development and delivery of Philo’s content recommendation system. • Collaborate closely with data roles in our business and finance teams (business insights, business analysts and financial analysts) to help them build a deep understanding of the Philo business, customers, and content trends. • Manage the data team: train, mentor and coach members of the data team, direct their work and support their career growth; identify the roles we need as we grow and hire fantastic people to fill those roles.

• Build and scale Data & Analytics team. • Responsible for building data + Generative BI strategy, governance, and delivery. • Identify systemic bottlenecks across ingestion, modeling, access, governance, and consumption. • Drive structural improvements to reduce time-to-insight while maintaining quality, security, and compliance. • Set clear delivery expectations, success metrics, and service levels for data products. • Define and execute a multi-year strategy for data and analytics platforms. • Establish clear architectural principles across platforms and data products. • Drive company’s evolution toward a federated or data mesh operating model. • Advance integration of Generative AI into data platforms. • Own design and operation of enterprise data platforms. • Build unstructured vector store and RAG capabilities. • Ensure platforms are reliable, secure, cost-effective, and scalable. • Drive data delivery for analytics and AI use cases. • Establish operating models balancing central capabilities with domain-led delivery. • Ensure data products delivered with clear ownership and measurable impact. • Partner with business leaders to define success metrics.

Develop and implement generative AI models to address complex challenges. Perform data manipulation, feature engineering, and prompt engineering while leveraging NLP techniques and statistical analysis for enhanced data integrity and model performance.