• Build and scale enterprise AI and machine learning capabilities across supply chain functions including logistics, distribution, planning, sourcing, and labor. • Translate business problems into well‐defined AI use cases, with clear success metrics and operational outcomes. • Define and operationalize standard frameworks for AI use‐case intake, prioritization, development, deployment, and lifecycle management. • Lead the end‐to‐end delivery of ML‐driven solutions, from problem framing and model development through production deployment and adoption tracking. • Own and continuously evolve the Supply Chain Data Science & AI roadmap, aligned with business priorities, AOP commitments, and long‐term capability goals. • Partner with data engineering, BI, and IT teams to embed AI solutions into dashboards, workflows, and operating processes, not standalone models. • Lead AI solution design using Microsoft technologies, including Azure AI, Azure Foundry, Copilot, and Power Platform. • Drive adoption of GenAI, copilots, and AI agents in a secure, scalable, and governed manner. • Evaluate, pilot, and integrate external AI tools and vendors, ensuring fit with enterprise data architecture, security standards, and long‐term scalability. • Establish best practices for model development, deployment, monitoring, explainability, and reuse, enabling repeatable delivery. • Mentor and develop analysts and data scientists, raising overall AI maturity and execution rigor across the organization. • Communicate progress, risks, and outcomes to senior stakeholders using clear, business‐focused language.

Role Description As a Principal Data Scientist, you'll be a senior analytical partner embedded across Growth and Membership Operations. Your work spans four domains: - Sales Operations (agent readiness, compliance, performance) - Marketing (prospect targeting, campaign attribution, spend optimization) - Telesales (call volume forecasting, agent productivity, workforce planning) - Membership Operations (enrollment processing, premium billing, CMS transactions, plan reconciliation) You will work across these teams to define ambiguous problems, determine what “good” looks like, and design the data systems that help us get there. You will combine deep technical skill, structured problem solving, and cross-functional partnership to turn messy operational challenges into clear, measurable, scalable solutions. Responsibilities and impact will include: - Framing ambiguous problems, defining what success looks like, and translating business challenges into measurable analytical strategies. - Owning and evolving scalable data models, pipelines, and core metrics that serve as the long-term foundations for operational performance in Sales and Membership Operations. - Building and iterating on analytical and modeling solutions, shipping quickly, learning from real-world feedback, and refining systems to drive measurable impact. - Leveraging emerging ML/AI tools thoughtfully, integrating them into production workflows where they add leverage, grounded in strong data fundamentals and clear business outcomes. Qualifications - Deep experience partnering with stakeholders across an organization to solve complex problems. - Comfort defining both the question and the measurement approach. - Ability to move fluidly between SQL, modeling, experimentation, and strategic conversations. - Enjoy building durable systems, not just running one-off analyses. - Collaborative and excited by hard problems. Requirements - Ability to thrive in a fast-paced, high-growth environment that values quick iteration. - 7+ years of individual technical contributor experience. - Strong SQL and experience working in modern data ecosystems (Snowflake, dbt, Python, Looker or similar). - Skilled at collaborating with cross-functional teams and influencing decisions with data-driven insights. - Comfort building scalable, maintainable data pipelines and performing deep statistical analysis, predictive modeling, or experimental design to drive business strategy. Desired Skills and Experience - Experience in healthcare, insurance, fintech, or other complex operational domains. - Familiarity with sales, marketing, or membership operations data or regulated environments. - Comfort performing live analysis or collaborative debugging with stakeholders. - Experience incorporating ML or AI tools into operational workflows. Benefits - Employer sponsored health, dental and vision plan with low or no premium. - Generous paid time off. - $100 monthly mobile or internet stipend. - Stock options for all employees. - Bonus eligibility for all roles excluding Director and above; Commission eligibility for Sales roles. - Parental leave program. - 401K program. - And more... Salary Range $133,942 - $187,083 annually plus eligibility for discretionary performance-based bonus paid out annually. Target bonus is 10% however the actual payout is based on the terms of the bonus plan. The total compensation for this role is $147,336 - $205,791 (base plus bonus).

• Oversee talent acquisition and recruitment operations, balancing quality, timelines, and stakeholder expectations • Acts as the primary point of contact for study teams, developing evidence-based country and site strategies, enrollment scenarios, and protocol optimization recommendations • Partners cross-functionally (including analytics and recruitment teams) to align feasibility, enrollment planning, and execution strategy throughout the study lifecycle • Delivers early feasibility insights, including initial enrollment timelines, country footprint, competitive landscape, and key assumptions to inform operational planning • Continuously refines country footprint, site strategy, and enrollment assumptions as protocols evolve through feasibility and start-up • Identifies protocol optimization opportunities using real-world data, investigator input, and patient insights • Supports investigator/site identification, database development, and global site intelligence coordination • Leads feasibility outreach, analyzes responses, and provides strategic recommendations for country and site selection • Develops analytics and scenario modeling to optimize site mix, enrollment timelines, diversity goals, and overall study performance • Partners with cross-functional teams to improve study start-up efficiency and recruitment cycle times • Owns delivery against defined KPIs and drives continuous improvement through data, innovation, and streamlined processes • Builds strong stakeholder relationships to enable effective and efficient study execution

Role Description Ignite Reading's mission is to teach every kid to read — and turning data into decisions is one of the most powerful ways the organization advances that work. In service of that goal, the Senior Data Scientist supports our partner-facing teams (Partnerships/Sales, Marketing, CX) as the Data & Analytics team's primary practitioner of advanced analytics, statistics, predictive modeling, and machine learning. This role is a senior individual contributor who applies DS/ML to generate actionable insights for the business, directly shaping how the organization acquires, retains, and grows partnerships with school districts nationwide. This person brings meaningful AI fluency to the team, using Claude, Cursor, and related tools to accelerate analytical workflows and build agentic workflows and Skills that extend the team's capacity. This role reports to the Senior Manager of Partner Analytics and works in close partnership with the broader Data & Analytics team. It is an exceptional opportunity for someone who wants to see their work make a real difference that changes lives. Key Responsibilities - Advanced Analytics & Statistical Modeling - Design and deliver end-to-end predictive models (including partner churn prediction, lead scoring, and partner health scores), translating complex business questions into rigorous, production-ready analytical solutions. - Develop and maintain attribution, marketing mix models and other marketing analytics frameworks that inform resource allocation and campaign strategy. - Apply statistical methods to identify leading indicators, drivers, and patterns across partner data; communicate findings and trade-offs clearly to technical and non-technical stakeholders. - Data Science & Machine Learning - Own the full ML lifecycle, from problem framing and feature engineering through model training, validation, deployment, and monitoring, ensuring models remain accurate, interpretable, and maintainable over time. - Establish and uphold repeatable standards for model development, documentation, and validation that enable consistent, trustworthy DS/ML output across the team. - Identify opportunities to apply ML and data science techniques to new business problems and proactively surface recommendations to leadership. - AI Engineering & Agentic Workflows - Build and deploy agentic workflows and Claude Skills that automate analytical and modeling tasks, accelerate DS/ML development, and extend the team's capacity. - Evaluate and recommend emerging AI tools and techniques relevant to data science and analytics. - Act as an AI resource and mentor for the broader analytics team, modeling effective AI-assisted development practices and actively contributing to a shared culture of AI literacy. - Collaboration & Communication - Partner closely with Sales, Marketing, and CX stakeholders to understand business context, identify and execute high-value analyses, and translate complex model outputs into clear, actionable insights and business narratives that directly shape organizational strategy and operations. - Bring structure, documentation, and process discipline to ambiguous technical domains, ensuring work is reproducible and knowledge is shared. Qualifications - 6-8+ years of demonstrated on-the-job experience across the entire ML lifecycle, building and deploying in production the kinds of models this role requires: churn prediction, propensity/upsell scoring, health scores, lead scoring, media mix modeling, or closely analogous work. - Strong quantitative foundation: proficiency in statistical modeling, experimental design, and analytical methods applied to real business problems. - Highly proficient in SQL and Python for data manipulation, analysis, and modeling. - Meaningful hands-on experience building agentic workflows, Claude Skills, or LLM-based automations using Claude, Cursor, or equivalent generative AI tools to accelerate analytical and ML workflows on the job. - Familiarity with AI operational practices (prompt libraries, guardrails, output validation) that enable consistent and reliable AI-assisted work. - A natural mentor and collaborator; a strong communicator who can explain complex technical concepts clearly to varied audiences. - A self-starter who works independently, persists until the job is done, and stays calm and resourceful in a high-growth, startup-like environment. - Passionate about our mission to teach kids to read. Preferred - Experience with student or education data and familiarity with PII handling requirements. Compensation & Benefits - Salary: $174,000 - Employee Stock Options - we want our success to be yours too - Medical, Dental, and Vision plans to support you and your well-being (80% employee coverage, 70% dependent coverage) - Short-term Disability (100% employer paid) - 401(k) retirement plans with company contribution - 12-weeks paid parental leave - Unlimited vacation days (+ 12 paid holidays) - Technology Stipend - Wellness Stipend - Voluntary Life Insurance - Professional Development Stipend