Data Analysis & Insights

• Analyze datasets from Google Search Console, Analytics, Ahrefs, SEMrush, and internal tools to uncover trends, correlations, and growth opportunities.

• Build predictive models to forecast keyword rankings, traffic potential, and content performance.

• Develop dashboards and visualizations (in tools like Looker Studio, Power BI, or Tableau) for SEO performance tracking.

SEO Experimentation

• Design and execute A/B tests for SEO hypotheses (e.g., title tag optimization, schema impact, internal linking).

• Measure causal effects of SEO changes using statistical methods such as regression analysis or Bayesian modeling.

Automation & Tooling

• Automate repetitive SEO reporting and keyword clustering tasks using Python, R, or SQL.

• Develop scripts or APIs to collect and process data from multiple SEO platforms.

Collaboration

• Partner with SEO strategists to translate analytical findings into actionable strategies.

• Work with developers to ensure tracking accuracy and SEO data pipeline integrity.

Research & Innovation

• Stay up to date with Google algorithm updates, AI-driven search (SGE, AI Overviews), and natural language processing (NLP) techniques.

• Explore how LLMs and AI-driven tools can influence SEO visibility and data interpretation.