Data Scientist Senior

NTT; Milano; In loco; EUR 40.000 - 70.000; Tempo pieno

Descrizione del lavoro

NTT DATA seeks a Senior Data Scientist with strong expertise in Generative AI, machine learning, and business acumen. Responsibilities include leading data science projects, collaborating with various teams, and innovating solutions to drive organizational efficiency and revenue.

Competenze

• 3-5 years of experience as a data scientist.
• Strong knowledge in Python and SQL.
• Familiarity with cloud ML implementations.

Mansioni

• Lead Data Science projects and ensure timely execution.
• Collaborate with data engineers for productionized ML pipelines.
• Engage with internal teams and external clients to maintain strong relationships.

Conoscenze

Python

SQL

Machine Learning

Deep Learning

Generative AI

Statistical Expertise

Tensorflow

Descrizione del lavoro

Responsibilities

The ideal candidate as Senior Data Scientist in NTT DATA will have a mix of skills including Generative AI hands-on capability (preferably on Azure / GCP and on-premise) engineering best practices, statistical expertise, Machine and Deep Learning skills and a strong business sense.

The Senior Data Scientist will work with fellow data scientists, data engineers, ML Engineers, product managers, business analysts, and stakeholders from other internal groups and from external clients.

He / She will be responsible for multiple projects, leading the Data Scientists and connecting with the stakeholders on client?s side, to ensure that tasks are on time and well executed.

Required Skills

• Experience of at least 3-5 years as data scientist;
• Strong Python (mandatory) and SQL coding;
• Knowledge of Java / Scala or C++ / R is a plus;
• Tensorflow and Pytorch knowledge with a focus over Computer Vision solutions;
• Knowledge of ML solutions architecture and Generative AI pipelines;
• Cloud and hybrid ML implementations;
• Incorporate new, cutting edge business intelligence, machine learning, and alternative data practices into wider organization to drive efficiencies and generate revenue;
• Own the full stack execution of data science projects from data wrangling, model development, presentation, measurement to deployment;
• Work with data engineers to produce fully productionized pipelines including data ingestion, cleaning, feature engineering and model training / prediction;
• Conduct research and analysis into reinsurance and advisory products to augment industry-standard models and develop new market offerings;
• Establish and maintain strong relationships with internal team members and external clients