Senior Data Analyst (AI & Advanced Analytics) – Job Description
PURPOSE AND SCOPE
Plan and deliver advanced data analysis and insights that support AI/ML initiatives and data-driven decision-making.
Partner with data science, engineering, and business teams to prepare, analyze, and operationalize data for predictive modeling and AI applications.
Ensure high-quality, reliable, and governed data assets aligned with enterprise data architecture and analytics standards.
PRINCIPAL DUTIES AND RESPONSIBILITIES
Conducts advanced data analysis to identify trends, patterns, and opportunities for AI and advanced analytics use cases.
Identifies and evaluates relevant data sources, including structured and unstructured data, to support modeling and reporting needs.
Performs exploratory data analysis (EDA), feature analysis, and data validation for AI/ML initiatives.
Develops and maintains dashboards, reports, and performance metrics to monitor business and model outcomes.
Partners with data scientists to support model development, including dataset preparation, feature engineering support, and evaluation analysis.
Collaborates with data engineering teams to improve data pipelines, data quality, and data accessibility.
Analyzes data discrepancies, resolves issues, and ensures consistency across datasets.
Supports experimentation and A/B testing, including design, analysis, and interpretation of results.
Translates analytical findings into actionable insights and recommendations for business stakeholders.
Works with data stewards to ensure alignment with data governance, quality, and compliance standards.
EDUCATION
Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, or related field required.
Master’s degree in a quantitative or analytical field preferred.
EXPERIENCE AND REQUIRED SKILLS
5 – 8+ years’ related experience; or a Master’s degree with 4+ years’ experience; or equivalent directly related work experience.
Strong proficiency in SQL and at least one programming language (Python or R).
Experience working with large datasets and cloud-based data platforms (AWS, Azure, Databricks, Snowflake).
Solid understanding of statistical analysis techniques and data modeling concepts.
Experience supporting machine learning and predictive analytics initiatives.
Proficiency with data visualization tools (Power BI, Tableau, or similar).
Ability to communicate complex analytical insights to business and technical stakeholders.
Familiarity with model evaluation metrics, feature engineering concepts, and experimentation frameworks preferred.
Exposure to Generative AI analytics (prompt performance, usage tracking, and evaluation) preferred.
