Data Scientist Senior

NTT; Napoli; In loco; EUR 40.000 - 65.000; Tempo pieno

Descrizione del lavoro

A leading company in the tech sector is seeking a Senior Data Scientist for their Napoli office. The successful candidate will have a solid background in AI technologies, particularly Generative AI. This position involves managing projects and collaborating with diverse teams to enhance organizational efficiency in data-driven initiatives.

Competenze

• 3-5 years of experience as a data scientist.
• Proficiency in Python (mandatory).
• Knowledge of Java / Scala or C++ / R is a plus.

Mansioni

• Manage multiple projects and lead data science teams.
• Collaborate with internal teams and external clients.
• Develop fully productionized pipelines with data engineers.

Conoscenze

Python

SQL

Machine Learning

Deep Learning

Generative AI

TensorFlow

PyTorch

Cloud ML

C++

Java

Descrizione del lavoro

Responsibilities

The ideal candidate for the Senior Data Scientist position at NTT DATA will possess a diverse skill set, including hands-on experience with Generative AI (preferably on Azure, GCP, and on-premise), engineering best practices, statistical expertise, and proficiency in Machine Learning and Deep Learning. A strong business sense is also essential.

The Senior Data Scientist will collaborate with fellow data scientists, data engineers, ML engineers, product managers, business analysts, and stakeholders from both internal teams and external clients.

He / She will be responsible for managing multiple projects, leading data science teams, and liaising with client stakeholders to ensure timely and effective project execution.

Required Skills

• At least 3-5 years of experience as a data scientist;
• Proficiency in Python (mandatory) and SQL;
• Knowledge of Java / Scala or C++ / R is a plus;
• Experience with TensorFlow and PyTorch, focusing on Computer Vision solutions;
• Understanding of ML solutions architecture and Generative AI pipelines;
• Experience with cloud and hybrid ML implementations;
• Ability to incorporate cutting-edge business intelligence, machine learning, and alternative data practices to improve organizational efficiency and revenue;
• Ownership of the entire data science project lifecycle, from data wrangling and model development to presentation, measurement, and deployment;
• Collaboration with data engineers to develop fully productionized pipelines, including data ingestion, cleaning, feature engineering, and model training/prediction;
• Conduct research and analysis related to reinsurance and advisory products to enhance industry-standard models and develop new market offerings;
• Establish and maintain strong relationships with internal team members and external clients.