Marketing Data Analyst

Overview We are looking for an exceptional Data Analyst to join the Coches.Net, Motos.Net and Milanuncios.com team. You will work as a member of a multidisciplinary team, collaborating closely with Product owners, cluster teams, data engineers and management team stake-holders (Marketing, Sales, Product, BizDev and other Operations teams). Your main mission is to define and execute analyses of several business contexts to identify trends, opportunities and problems to improve the offering and services we provide.

These will be your functions :

Responsibilities Identify, analyse and interpret KPIs and Health Metrics related to our users and customers, creating dashboards and visualisations to monitor them.

Identify trends, risks and opportunities to provide insights that can make recommendations on how to improve the different initiatives of the vertical.

Create powerful insights using advanced analytics to improve knowledge of our users and customers.

Actively participate in the discovery and development of advanced analytical models (such as clustering and predictive models), and their implementation in business use cases, such as customer segmentation, propensity models for upselling, downselling, and churn prediction.

Qualifications 3+ years of experience in eCommerce, an online company.

Advanced knowledge of SQL and relational databases.

Advanced knowledge of Python and / or R for data analysis (e.g. pandas, numpy, matplotlib), and advanced analytics (e.g. scikit-learn).

Advanced user of at least one visualization tool such as Tableau and / or QlikSense.

Analytical skills : ability to interpret data, extract relevant insights and translate business questions into analytical needs.

Experience working with sales, operations, and strategy teams.

Good knowledge of basic machine learning algorithms (e.g. clustering, classification, regressions).

Some experience with big data technologies (e.g. Databricks, data lakes).

Some knowledge of data engineering tools (e.g. Airflow, DBT).

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