McKinley Marketing Partners · 1 month ago
Senior AI Data Analyst
McKinley Marketing Partners is seeking a Senior AI Data Analyst to support their rapidly growing Digital organization. The role involves analyzing data for machine learning models, building analytical frameworks, and visualizing AI feature performance to drive business decisions.
ConsultingArt & CreativeMarketingDigital MarketingGraphic Design
Responsibilities
Research, prototype, and build analytics solutions and visualizations to support the AI/ML pipeline, from data ingestion through model deployment
Analyze training and production data for machine learning models to identify data quality issues, drift, feature importance, and behavioral shifts
Design and execute robust experimental frameworks (A/B tests, holdout tests) to quantify the impact of AI-driven features and digital product changes
Develop clear KPI definitions and measurement strategies for AI features and digital initiatives, ensuring consistency across teams
Create and maintain dashboards and visual reports in Python and Power BI that communicate trends, anomalies, and opportunities to business stakeholders
Collaborate closely with data scientists, ML engineers, product managers, and digital leaders to translate complex analytical findings into actionable recommendations
Continuously refine analytical models and reporting as new data sources, features, and products are introduced
Stay current with emerging tools, libraries, and techniques in analytics, data engineering, and AI observability, and introduce best practices into the team
Ensure timely delivery of high-quality analysis and documentation in a fast-paced, agile environment
Qualification
Required
Strong knowledge of statistical techniques and advanced mathematics (e.g., hypothesis testing, regression, experimental design, time-series analysis)
3+ years of experience as a data analyst, data engineer, or data scientist working within the Databricks ecosystem (Azure Databricks preferred)
5+ years of experience applying statistical techniques to analyze, segment, and visualize data, with hands-on experience in experimental design, KPI calculation, and A/B testing
4+ years of experience manipulating and analyzing large-scale datasets using Python, PySpark, and/or SQL
Expert-level experience with data visualization tools and libraries (e.g., Python data viz stack, Power BI) to create interactive dashboards and compelling visual narratives
Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or related field; or equivalent practical experience