Data Scientist Senior

NTT DATA Europe & Latam; Calopezzati; In loco; EUR 40.000 - 70.000; Tempo pieno

Descrizione del lavoro

NTT DATA is hiring a Senior Data Scientist to lead data science projects and collaborate with internal and external teams. The ideal candidate will have strong skills in Python and SQL while leveraging cloud ML implementations and Generative AI solutions. This role is central to driving data-driven efficiencies and enhancing market offerings.

Competenze

• 3-5 years of experience as a data scientist.
• Strong Python and SQL coding skills required.
• Knowledge of ML solutions architecture and Generative AI pipelines.

Mansioni

• Responsible for multiple projects, leading Data Scientists and connecting with stakeholders.
• Own the full stack execution of data science projects.
• Conduct research and analysis into reinsurance and advisory products.

Conoscenze

Python

SQL

Tensorflow

Pytorch

Machine Learning

Deep Learning

Generative AI

Strumenti

Java

Scala

C++

R

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.

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