Director of Analytics- Outcomes & Experimentation

Role Summary
The Director of Outcomes and Experimentation will build the measurement infrastructure Kia needs to make faster, more confident marketing decisions. This role leads measurement standards, QA, and workflow automation by connecting analytics, media operations, data science, engineering, vendors, and client stakeholders.

Business Impact
•    Builds scalable measurement practices that improve decision confidence and consistency.
•    Increases team capacity by automating repetitive analytical and operational workflows.
•    Creates a standard measurement tech stack foundation across channels and use cases.
•    Turns proven workflows into reusable agency capabilities.

Key Responsibilities
Measurement QA and Data Governance
•    Build and govern QA standards across data ingestion, transformation, modeling, reporting, and visualization.
•    Define validation checkpoints, ownership, escalation paths, documentation requirements, and acceptance criteria.
•    Develop frameworks to identify and resolve discrepancies across platforms, ad servers, analytics tools, databases, and reporting systems.
•    Lead root-cause analyses with internal teams, clients, technology partners, and vendors.
•    Implement monitoring and controls to catch data-quality issues before they affect deliverables or decisions.
•    Translate measurement outputs into practical solutions while documenting limitations, dependencies, and appropriate use cases.
Automation and Scalable Workflows
•    Design scalable workflows that streamline data collection, processing, modeling, reporting, and visualization.
•    Automate repeatable tasks to improve speed, quality, consistency, and team capacity.
•    Keep workflows adaptable as measurement needs, platforms, and business priorities evolve.
Marketing Technology Stack - Standardization 
•    Define and maintain standard measurement technology architecture across analytics, data processing, storage, modeling, and visualization.
•    Set selection criteria and governance standards for new technologies and vendor solutions.
•    Lead technical reviews and proof-of-concepts for measurement, data, automation, and MarTech tools.
•    Turn successful prototypes into reusable capabilities with clear users, use cases, requirements, and value propositions.
Client Leadership 
•    Serve as a trusted advisor to marketing, media, and executive stakeholders on advanced measurement infrastructure & technologies.
•    Lead measurement discussions, workshops, and planning sessions while managing risks, expectations, and stakeholder alignment.
Cross-Functional & Team Leadership Expectations
•    Lead multidisciplinary teams through complex technical initiatives with clear roles, decision points, and accountability.
•    Translate business needs into actionable plans that connect technical requirements, timelines, risks, and success criteria.
•    Drive cross-team execution from planning through launch, including testing, adoption, and post-launch validation.
•    Create structure around ambiguous technical and business problems, balancing innovation with reliability, maintainability, adoption, and scale.
•    Coach team members through clear delegation and technical guidance while fostering curiosity, accountability, analytical rigor, and continuous improvement.

Qualifications
Required
•    8+ years of experience in MarTech, analytics engineering, data engineering, marketing analytics, data science, or a related field.
•    Experience leading technical analytics or measurement initiatives across multiple platforms, datasets, and stakeholder groups.
•    Ability to communicate technical tradeoffs, measurement limitations, implementation risks, and business implications clearly to executive, client, technical, and non-technical audiences.
•    Bachelor’s degree in computer science, engineering, statistics, data science, information systems, mathematics, or a related field, or equivalent experience.
Preferred
•    Familiarity with SQL and modern data platforms or analytical tools such as Snowflake, BigQuery, Python, R, SAS, or comparable technologies.
•    Experience managing technical vendors, platform partnerships, cloud integrations, or software development practices.
•    Experience taking an internal tool from prototype through adoption, governance, and ongoing product management.
•    Agency or client-side marketing analytics experience, particularly in media measurement, experimentation, MarTech, or outcomes-focused analytics.