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Data Scientist Senior
Job summary
A leading data science firm in Bari seeks a Senior Data Scientist to lead projects, collaborating with teams to execute data science initiatives. Candidates should have 3-5 years of experience, strong Python and SQL skills, and knowledge of Generative AI. This role involves owning the full project lifecycle from data wrangling to deployment and establishing strong client relationships.
Qualifications
- 3-5 years of data scientist experience is required.
- Strong coding skills in Python and SQL are mandatory.
- Knowledge of machine learning solutions architecture is necessary.
Responsibilities
- Lead multiple projects and connect with stakeholders.
- Own full execution of data science projects.
- Collaborate with data engineers on productionized pipelines.
Skills
Tools
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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
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.