I’m a Data Analyst with a strong business and marketing background, focused on marketing analytics, experimentation, and data-driven decision-making.

Before transitioning into data, I founded and led my own branding and web design agency, working closely with businesses on positioning, digital products, and growth strategy. Over time, I realized that the most impactful decisions weren’t driven by intuition or aesthetics alone — but by data, experimentation, and measurable performance.

That insight led me to deepen my skills in programming, analytics, and applied machine learning, bridging my creative and strategic background with Python, SQL, statistical analysis, and experimentation frameworks. Today, I specialize in translating data into clear business actions, especially in growth, acquisition, and optimization contexts.

• Marketing analytics: LTV, CAC, ROMI, cohort & retention analysis
• Experimentation & A/B testing: hypothesis design, statistical validation, decision-making
• Funnel, conversion & user behavior analysis
• SQL-driven analysis on relational databases
• Applied machine learning for segmentation, pattern discovery, and insight generation
• Data storytelling for business and stakeholders

• Python (pandas, numpy, scipy, basic ML workflows)
• SQL (analytical queries, joins, CTEs, aggregations)
• Statistics & A/B Testing
• Machine Learning (applied) — clustering, feature analysis, exploratory modeling
• Data Visualization (Tableau, matplotlib, seaborn, Plotly)
• Jupyter Notebooks
• Business-oriented analysis & insight communication

• Marketing Cohort Analysis
  End-to-end cohort, LTV, CAC, and ROMI analysis to identify the most profitable acquisition channels and retention patterns, with clear budget allocation recommendations.

• A/B Testing Case Study — Experimental Validation & Decision-Making
  Complete experimentation workflow including hypothesis formulation, metric selection, statistical testing, and business-oriented conclusions.

• CallMeMaybe — Operator Performance & Experiment Analysis
  Funnel analysis and experiment evaluation to assess operator efficiency and support product and operational decisions.

• Machine Learning Case Study — Customer Segmentation & Insight Discovery
  Applied machine learning project focused on exploratory modeling and clustering to identify behavioral patterns and user segments, supporting data-driven decision-making rather than pure model performance.

• SQL Bookstore Analysis
  Advanced SQL analysis on relational data to extract insights on user behavior, content performance, and engagement, demonstrating strong querying and analytical reasoning.

I’m interested in data analyst roles within tech and marketing-driven companies, especially teams that value experimentation, analytics, and AI-enabled growth.

I thrive in environments where data directly informs strategy, product decisions, and performance optimization.

📫 Feel free to explore my repositories or reach out if you’d like to discuss analytics, experimentation, or data-driven marketing.