Key Accountabilities

She/he will be carrying on the following activities:

• Build robust and efficient production data pipelines, ETL and EL workflows and optimize current ones, to assure continuous delivery of accurate and quality KPIs to end users.
• Prototype, develop and operationalize ML models to improve Customer Experience and Conversion Probability, working with Product Development teams.
• Generate insights using multiple data sources from our on-premises and cloud IT, create compelling stories using Powerpoint and Jupyter Notebooks, support Business leadership with ad hoc analysis.
• Design, deploy and maintain scalable dashboards for the top management and other internal/external stakeholders, with a focus on the backend data infrastructure.
• Improve and optimize current web KPIs and alert-systems using automation techniques and machine learning, write programming code ready to be integrated in production, contribute to the creation and improvement of new data sources.
• Be a pivotal player involved in all the data science projects across the organization, working with PMs, Engineers and Analysts from different departments both at Gucci and Kering level.
• Be a Data Science evangelist, spreading analytics culture at different levels, from code readability and documentation, to storytelling and knowledge sharing.

Job Requirements:

• At least 3 years of experience in Data Scientist / Data Engineering roles, in fast paced environments.
• Programming proficiency in Python and data analysis modules : Pandas, NumPy, SciPy, StatsModels and Scikit-Learn.
• Good knowledge of SQL/DML with a focus on scalability, building fast and efficient queries or data structures (indexing, clustering and partitioning).
• Data engineering skills, ETL, EL, data pipelines (batch and stream jobs) and relative technologies.
• Cloud computing, mainly GCP. Experience on AWS appreciated.
• Knowledge of Data visualization tools such as Data Studio and Tableau.
• Experience with web APIs.
• Experience in operationalization of Machine Learning models and virtualization frameworks such as Docker.
• Ability to create and manage cross functional relationships.
• Positive, enthusiastic, able to take initiative with a geek-can-do attitude.
• Proficient in English (both written and spoken).

Nice-to-have:

• Previous experience in a Data science consultancy team, or Digital Marketing units is a big plus.
• Knowledge of one or more of the following Apache frameworks: Airflow, Beam, Spark.
• Experience with Google Cloud Platform Services: GCS, Pub/Sub, Cloud Functions, Composer, Data Flow and Big Query.
• Experience in one or more of the following tools: Google Tag Manager, Google Cloud Platform, Firebase, G4, MicroStrategy.
• Expertise with Machine Learning supervised (linear, non-linear regression, ensemble decision trees, gradient descent boosting) and unsupervised models (K-means clustering).
• Knowledge of other Machine Learning/AI fields (neural networks, natural language processing, association rules etc..).
• Other programming languages (Bash and JavaScript are very important for us).