Internship Opportunities in Global Data Science - Milano, Italia - Groupe Kering

Groupe Kering

Azienda verificata

Milano, Italia

1 settimana fa

Inviato da:

Piero Bianchi

Reclutatore di talenti per beBee

StageSHIP

Descrizione

Summary

Are you ready to start your GUCCI Journey?

Join the Digital Teams in our MILAN Offices

Stop just dreaming. Start dream-making with us

Gucci is a one-of-a-kind place in which to express yourself, being who you are. A place where your unique talents are empowered. Read on to find out more

We're looking for someone driven by passion and determination. Here, you'll be given the unique chance to express your talent and be part of a community in which to build the best version of yourself

Job Description:

Where and when could you start the internship with us?

Starting from October 2023, we will offer an internship opportunity in the Data Science team.

Machine Learning Internship

Key Accountabilities:

Model Deployment and Integration: The intern will work on deploying machine learning models into production environments. They will gain experience in integrating models with existing software systems, creating APIs for model inference, and ensuring compatibility and scalability.
Data Pipeline Development: The intern will contribute to the development of data pipelines that support the machine learning process. This involves tasks like data ingestion, preprocessing, and transformation to prepare the data for model training and inference.
Model Monitoring and Maintenance: The intern will learn to monitor and maintain deployed machine learning models. They will implement monitoring solutions to track model performance, detect anomalies, and address issues such as data drift or concept drift.
Collaboration with Data Scientists and

Software Engineers:

The intern will collaborate with data scientists to understand modeling requirements, extract insights, and align ML engineering efforts with data science goals.

They will also work closely with software engineers to integrate models into production systems effectively.

Infrastructure Optimization: The intern will explore optimization techniques to improve the efficiency and scalability of machine learning systems. This may involve optimizing model inference speed, memory usage, or resource allocation using techniques like model quantization or distributed computing.
Documentation and

Knowledge Sharing:
The intern will maintain clear and organized documentation of their work, including code, model architecture, and deployment procedures. They will also have opportunities to share their learnings and experiences through documentation, presentations, or knowledge-sharing sessions.

Continuous Learning and Exploration: The intern will stay updated with the latest advancements in ML engineering by exploring new techniques, frameworks, and best practices. They will proactively seek opportunities to enhance their skills and contribute innovative ideas to the team.

What will you learn with us?

Data Ingestion and Extraction: The intern will learn techniques for collecting and extracting data from various sources, such as databases, APIs, and streaming platforms. They will gain handson experience in designing efficient data ingestion pipelines and ensuring data quality during the extraction process.
Data Processing and Transformation: The intern will learn data processing techniques using frameworks like Apache Spark or Apache Hadoop. They will gain experience in transforming and cleaning data, handling data quality issues, and performing data wrangling tasks to prepare data for downstream analysis and reporting.
Model Deployment and Scalability: The intern will learn how to deploy machine learning models into production environments, ensuring scalability and efficiency. They will gain experience in deploying models on our own DSML platform Databricks.
Data Pipelines for ML: The intern will work on building data pipelines that facilitate data ingestion, preprocessing, and transformation for machine learning tasks. They will gain experience in handling largescale datasets, integrating data from various sources, and ensuring data quality throughout the pipeline.

Data Science Internship

Key Accountabilities:

Data Collection and Preparation: The intern will gather relevant datasets from various sources, clean and preprocess the data, and ensure its quality and integrity for analysis.
Exploratory Data Analysis: The intern will perform exploratory data analysis (EDA) techniques to understand the data, identify patterns, outliers, and relationships, and gain insights that can guide further analysis.
Data Visualization and Reporting: The intern will create compelling visualizations and interactive dashboards to effectively communicate data findings, present insights to stakeholders, and contribute to comprehensive reports summarizing the results and recommendations.
Collaboration: The intern will participate in collaborative data science projects, working alongside team members, consultants or other interns. This will involve contributing ideas, sharing insights, and collectively solving datarelated challenges.
Documentatio