Corporate Experience

Internships

Links available below

DATA (2025)

Data Analytics Engineer Intern

Managed and scheduled Airflow pipelines, containerized in Docker and version‑controlled in Git, to transform raw event logs into analytics‑ready tables.
Participated in Python + SQL models feeding Deezer’s marketing product KPIs.
Published Tableau dashboards that give Stakeholders a self‑serve view of engagement metrics.
Build interactive Tableau dashboards (MAU, retention, skip-rate, revenue) for Marketing... Iterate with stakeholders and automate daily refreshes.
Used Scala and Java Spark jobs to accelerate heavy joins and nightly aggregates.
Pull, clean and aggregate large user-event datasets every day with Python & SQL, laying a solid statistical foundation for later analysis or modelling.
Deep-dive into user-behaviour datasets (SQL, Python,...) to surface actionable insights
Combined engineering discipline with hands‑on modelling to convert data into fast, actionable product and operations decisions.
IDE: Intellij
MONDAY usage for work management
Designed a skip‑probability model in Python, logged with MLflow‑style tracking, and surfaced scores to the ranking team.

Amazon Business | Business Intelligence Analyst and Demand Generation (2023)

Engaged with potential clientele to understand their needs, utilizing this data to help refine the value proposition of Amazon Business, aiding in the enhancement of customer acquisition strategies
Led a transformational project to convert a crucial offline DG performance report into an automated online dashboard, significantly improving real-time data accessibility, analysis, and operational decision-making.
Orchestrated seamless communication between the Munich and USA teams on a marketing project, gathering vital feedback from both sides, and meticulously overseeing the application of project deliverables to ensure alignment with objectives and maximize impact.

Operations (2024)

Utilized SQL and Python for data analysis to provide actionable insights, aiding in critical decision-making and strategy formulation.
Engaged in real-time, impactful projects to reimagine the movement dynamics, enhancing operational efficiency and customer satisfaction.
Dived deep into the vast operational intricacies of Uber, playing a crucial role in addressing key strategic challenges through data analytics and creative problem-solving.
Experimented with new product features and operational strategies, such as pricing adjustments and demand segmentation, to improve overall operational effectiveness.
Creation of template and UI using HTML for diverse projects

Links to projects are available below

Market Research (2022)

Conducted comprehensive market research to understand user segments, utilizing statistical analysis to interpret data.
Collaborated with the product development team to provide data-driven insights, aiding in the creation of a more user-centric product.
Used qualitative and quantitative analysis with SPSS software.
Developed strategic recommendations for the studied company.
Developed skills in market research and data analysis.

Data Science Project (2023)

Leveraged machine learning algorithms to analyze sales data and customer feedback, identifying opportunities for menu optimization.
Presented data-driven recommendations to stakeholders, leading to a 20% increase in customer satisfaction ratings.
Successfully reduced operational costs by 30% within 3 months through innovative data analysis and process optimization.
Drove a 40% increase in benefits over 4 months by implementing advanced predictive analytics and data-driven decision-making strategies.

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