• Provides leadership, strategic direction, and oversight of APA’s applied science and technology advocacy portfolio • Designs and leads advocacy campaigns advancing evidence-informed federal policy on technology policy • Builds and sustains relationships with executive-branch and congressional stakeholders • Drafts and negotiates high-stakes advocacy materials for diverse stakeholders • Monitors and analyzes federal legislation and regulations for impact on psychology • Serves as primary advocacy partner to members of the Psychology Team • Collaborates with cross-functional teams to advance APA priorities

• Own the Outcome: Hold end-to-end accountability for your pod’s results — product milestones, revenue targets, and customer impact. • Translate and Execute: Translate the company’s vision into your pod's product roadmap and delivery plan. • Own Positioning and Messaging: Develop and maintain segment-specific positioning, ICP definitions, buyer personas, and messaging frameworks. • Design the Work: Before your pod builds anything, you've defined the problem, pressure-tested the solution space, and structured the work for speed and quality. • Lead Voice of Customer and Market Intelligence: Run VOC and VOM programs that translate real buyer signals into sharper positioning and stronger product direction. • Lead from the Front: Coach and direct pod members day to day with the authority of a player-coach. • Drive Revenue: Own the commercial outcomes for your pod's domain. • Navigate the System: Build strong working relationships with partner groups to align on standards, unblock dependencies, and move fast without creating downstream problems. • Build AI-Native: Champion the active use of AI and automation tools inside your pod. • Communicate the Story: Represent your pod's work, decisions, and outcomes clearly to senior leadership and cross-functional partners.

Role Description You will lead the team that turns TailorCare’s data into decisions: who we reach, how we target outreach, which care pathway we recommend, and how we forecast clinical and financial outcomes. This is the ML and decisioning core of the company. The models your team ships directly drive patient engagement, surgical avoidance, and partner savings. TailorCare is growing fast. We are adding payers and markets quickly, and the systems and team you own have to scale with that pace. We need a leader who can deliver against near-term launch commitments while building for an order of magnitude more volume, grow and level a team through that change, and stay effective when priorities shift underneath them. Comfort with ambiguity and a bias toward execution matter as much as technical depth here. This is a player-coach leadership role. Our teams own and drive outcomes, not task lists. You will be accountable for results, with the latitude and the obligation to decide how your team gets there. You will own the team strategy and delivery, set the technical bar, and stay close enough to the work to make architecture and modeling calls yourself. Primary Responsibilities - Lead a team of outcome-driven data scientists and ML engineers, with direct accountability for delivery, technical quality, and growth. - Drive cross-functional partnership with Medical Economics, Clinical Operations, Product, and the Data & Intelligence Foundation team. - Own the interface between modeling work and the platform and infrastructure it runs on. - Make build-versus-buy and architecture calls, set the technical bar, and stay hands-on enough to make modeling decisions yourself. - Other duties as assigned. Qualifications - Master’s or PhD in a quantitative field (computer science, statistics, machine learning, operations research, applied mathematics, economics, or a closely related discipline). This is a requirement for the role; a PhD with applied, production-oriented research is a strong plus. - A demonstrable history of ML systems you shipped to production that moved a business or clinical metric, with the specifics of what you built, what changed, and how it was measured. - Evidence of delivering against hard external deadlines and managing data-dependency risk without slipping quality. - A record of building and growing high-performing technical teams, including hiring, leveling, and developing data scientists and ML engineers. - Experience owning a model portfolio across its full lifecycle, retiring or refactoring models that no longer earn their place. - Ability and willingness to travel up to 10% as needed for onsite meetings, team collaboration, and company events. Preferred Qualifications - Healthcare, payer, or value-based care experience, and familiarity with HIPAA-regulated data. - Experience translating actuarial or medical-economics concepts into model features and targets. - Published or peer-reviewed work in applied ML, forecasting, or causal inference. - Ability and willingness to travel up to 10% as needed for onsite meetings, team collaboration, and company events. Skills - Deep applied ML: supervised learning on tabular and structured data, gradient-boosted trees (XGBoost, LightGBM), feature engineering, calibration, and rigorous offline and online evaluation. - Production ML engineering: model packaging, deployment, monitoring, drift detection, and retraining pipelines. You own model quality in production, not just in a notebook. - Strong software engineering fundamentals: Python, SQL, version control, testing, and code review standards you can set and enforce. - Modern data and ML platform fluency: Databricks, dbt, and AWS (S3, Postgres, DynamoDB). Comfortable making build-versus-buy and architecture calls. - Experimentation and causal rigor: A/B testing, uplift modeling, and the judgment to distinguish correlation from decision-relevant signals. - Sound judgment on where newer methods (LLMs, agents, feature augmentation from external signals) add measured lift versus where they add cost and risk. - You lead with the recommendation and state risks plainly, escalate risk early, and decide fast. Communication is concise and structured. Benefits - Meaningful Work: We are dedicated to our mission and deeply value our patients and each other. Each day offers the opportunity to make a positive impact. - Work Environment: We operate as a remote-first company with options for a hybrid work model in Nashville. - Time Off: Our generous paid time off (PTO) and holiday plans ensure you have ample time to rest and recharge. - Family First: We offer paid parental leave and support a healthy work-life balance, encouraging flexibility and autonomy. We love talking about our family and pets! - Comprehensive Benefits: From Day 1, employees enjoy medical, dental, vision, life, and disability insurance, wellness resources and an employer HSA contribution. - Fair Compensation: We are committed to equitable pay for all team members and support your future goals with a 401k plan that includes employer matching. - Community: We foster an inclusive environment where you can rely on your teammates, share honest feedback, and feel comfortable being your authentic self at work each day.

Role Description Global Director Market Data & AI is a strategic leadership role with a dual mandate: globally, shaping market data as a critical enterprise asset, and locally, translating data and AI strategy into scalable business impact across multiple priority markets, with the U.S. and Canada as core markets. This role is central to building a more predictive, connected, and insight-led commercial engine. The successful candidate will turn trusted market data into competitive advantage by enabling analytics, AI, and decision-making at global scale while ensuring business teams can act on harmonized, high-quality, and activation-ready data. By combining global domain ownership with multi-market execution, this role bridges strategy and delivery. It ensures that enterprise standards are shaped by real market needs, while local initiatives benefit from scalable governance, reusable data products, and cross-market best practices. As AI becomes a core operating layer for commercial decision-making, market data is evolving from reporting support into continuous commercial intelligence. This role will help shape that future by strengthening data foundations, improving governance, and enabling intelligent systems that support faster insight generation, better investment decisions, and scalable growth across markets. Qualifications - Master’s degree in business, Economics, Data Science, Statistics, or a related field; bachelor’s degree with equivalent experience also considered. - Proven experience as a Business Data Domain Owner with end-to-end accountability for domain strategy, governance, data quality, priorities, and business alignment. - Experience managing market data vendors, budgets, contract negotiations, provider consolidation, and license optimization. - Experience defining and maintaining commercial data dictionaries, metadata, lineage, data caveats, and usage standards. - Strong knowledge of data governance frameworks, data quality controls, and their practical application in large commercial organizations. - Track record of translating business outcomes into analytics, automation, and AI use cases enabled by high-quality, well-structured, and compliant market data. - Practical understanding of responsible AI principles, data privacy, third-party data usage rights, and governance requirements for compliant AI deployment. - Experience partnering with IT, product, analytics, and business teams to integrate market data into enterprise platforms such as Snowflake, Azure, or Databricks, moving data and AI use cases from concept to scalable adoption. - Demonstrated success leading data and AI initiatives from strategy to deployment and adoption, including value tracking, user enablement, and measurable impact on business outcomes. - Experience with AI-enabled process redesign, including working backwards from business outcomes, defining data and workflow requirements, and supporting adoption across markets or business units. - Ability to shape structured and unstructured data requirements, semantic definitions, metadata, and interpretation rules needed for analytics, automation, and AI-powered decision support. - Strong knowledge of GDPR, third-party data usage rights, and license management in a regulated environment. - Strong leadership, communication, and stakeholder management skills. - Strong ability to lead human-centered transformation, helping teams understand how AI will augment work, reduce manual effort, and shift contribution toward higher-value activities. - Fluent English required; additional languages (Spanish, Polish, German) are an asset. Requirements - Define the global vision, roadmap, and success measures for market data, including acquisition, governance, activation, and value realization in partnership with Insights & Analytics, Marketing, Sales, Finance, IT, Procurement, and external data providers. - Define and enforce global governance standards, taxonomies, data policies, and quality frameworks across the full data lifecycle — from ingestion to consumption — ensuring compliance with GDPR, data privacy, licensing terms, and applicable regulatory requirements in partnership with Legal and IT. - Own the global market data quality and enrichment strategy, including standards, matching algorithms, and scoring models that keep profiles accurate, deduplicated, complete, and fit for activation and AI use. - Partner with cross-functional teams—including Digital, Data, Technology, Customer & Commercial, Media, and Operating Units—to design global-to-local data flows, integration models, and activation strategies that connect structured and unstructured data across markets. - Establish and coordinate a global network of Data Owners and Business Data Stewards, providing clear accountability, escalation paths, and decision-making forums across markets. - Co-shape the Master Data Strategy, ensuring Market Data aligns with Product, Customer, and Consumer master domains — harmonizing market and channel definitions across providers and systems to enable downstream analytics and AI use cases. - Ensure Market Data is AI-ready by design — with robust quality, consistent structures, documented lineage, compliant usage rights, and clear semantic standards — so data can reliably fuel analytics, automation, and intelligent action in collaboration with I&A Home, IT, Legal, and others. - Define and execute a multi-market data and AI roadmap aligned with commercial priorities, with the U.S. and Canada as core markets and a focus on scalable, reusable data products, AI-enabled workflows, and measurable business outcomes. - Translate global data domain strategies into effective market execution, capturing feedback from priority markets to continuously strengthen enterprise-wide strategy. - Identify, prioritize, and lead data and AI initiatives that deliver measurable business value, including revenue growth, cost optimization, stronger consumer engagement, and faster commercial decision-making. - Work backwards from priority market outcomes to redesign data-enabled and AI-supported processes, ensuring that information flows, data connections, and decision points are practical for markets to adopt and scalable across product teams. - Integrate process design, information architecture, data architecture, and user experience considerations to create intelligent, user-friendly workflows that can be deployed and continuously improved across priority markets. - Oversee governance, management, and quality for procured and internal data assets, partnering with IT, Legal, Privacy, and business stakeholders to ensure secure, compliant, and value-driven data usage. - Collaborate with global and market teams across Marketing, Sales, Supply Chain, Regulatory, Digital, Finance, and Commercial Excellence to understand business needs and translate them into actionable data capabilities. - Partner with IT to enable scalable, secure, and accessible data platforms that connect business requirements with technical delivery, support cross-market adoption, and enable responsive information flows from data source to business action. - Lead cross-functional working teams and human-centered change management, creating a clear vision for how AI will augment work, reduce manual effort, and help teams adopt new ways of working with confidence. Benefits - Employees can expect to be paid a salary between $173280- 259920. - Additional compensation may include a bonus or commission (if relevant). - Other benefits include health care, vision, dental, retirement, PTO, sick leave, etc.