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  • Linz,Vienna Austria · open to relocation

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marynasaid/README.md

Hi, I'm Maryna Said

Second-year Artificial Intelligence (BSc) student at Johannes Kepler University Linz, working on causal inference and customer analytics for fashion and retail.

I measure what campaigns, discounts and promotions really change in customer behaviour, by segment, and turn the results into decisions and dashboards.

Projects

Tools: Python (pandas, NumPy, scikit-learn, EconML) · Power BI (DAX, data modelling) · causal inference · uplift modelling · A/B testing · LLM pipelines (Gemini, Mistral) · NLP

LinkedIn

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  1. targeted-markdowns-zalando targeted-markdowns-zalando Public

    Which products still need a discount? Targeted markdowns on Zalando data: +10.6% gross profit vs current pricing

    Python

  2. uplift-small-campaigns-starbucks uplift-small-campaigns-starbucks Public

    Reliable customer targeting from small campaigns: Starbucks offer data, 55 of 100 extra purchases kept with 30% of offers

    Python

  3. uplift-x5-retailhero uplift-x5-retailhero Public

    Who did an SMS campaign really move? Uplift modelling on 200,000 X5 RetailHero customers: one segment responded 3x the average

    Python