Base

Data Scientist

livorno, toscana, Italy Azienda: JR Italy Cliente / Datore di lavoro: Avangarde Group
Pubblicato: 19.05.2026
Data di chiusura: 03.07.2026
Referenze lavorative: 80155a50528d494d6e2ee0dac2ccc12b

Informazioni sul lavoro

Posizione
livorno, toscana, Italy
Azienda
JR Italy
Cliente / Datore di lavoro
Avangarde Group
Referenze lavorative
80155a50528d494d6e2ee0dac2ccc12b
Tipo di elenco
Base
Permesso di lavoro UE richiesto
No
Pubblicato
19.05.2026
Data di chiusura
03.07.2026

Descrizione del lavoro

Principali compiti e responsabilità

Analisi e preparazione dei dati e sviluppo di modelli di machine learning e algoritmi predittivi a supporto delle strategie di business. Validazione, rilascio e miglioramento continuo delle soluzioni AI, con estrazione di insight e supporto a decisioni data-driven.


Requisiti tecnici

  • Python (pandas, numpy, scikit-learn, xgboost, lightgbm)
  • Machine Learning: clustering, regressione, decision trees, SVM
  • Data preparation & feature engineering
  • DBMS: SQL (PostgreSQL, MySQL, Oracle)
  • Esperienza su modelli predittivi per business
  • Autonomia su dataset complessi e non strutturati


Cosa offriamo

  • Opportunità di impiego a tempo indeterminato
  • Percorsi di formazione professionale di alto livello, erogati attraverso il nostro programma interno Academy
  • Benefit (Ticket Restaurant)
  • Retribuzione commisurata ai livelli di esperienza acquisiti
  • Possibilità di entrare in contatto con professionisti dalla comprovata esperienza, all'interno di un'azienda leader nel mercato di riferimento e con oltre venti anni di attività svolta


La candidatura si intende rivolta a candidati di ambo i sessi ai sensi della Legge n° 903/77.

Abilità

apply blended learning apply for research funding apply research ethics and scientific integrity principles in research activities build recommender systems Business Analytics Business Intelligence collect ICT data communicate with a non-scientific audience Computational Biology Computer Simulation conduct research across disciplines create data models Data Engineering data ethics Data Mining Data Models data quality assessment Data Science data visualisation software define data quality criteria deliver visual presentation of data demonstrate disciplinary expertise design database in the cloud design database scheme develop data processing applications develop professional network with researchers and scientists Digital Curation disseminate results to the scientific community draft scientific or academic papers and technical documentation empirical analysis establish data processes evaluate research activities execute analytical mathematical calculations Hadoop handle data samples Healthcare Analytics image recognition implement data quality processes increase the impact of science on policy and society information categorisation Information Extraction integrate gender dimension in research integrate ICT data interact professionally in research and professional environments interpret current data LDAP LINQ make data-driven decisions manage data manage data collection systems manage findable accessible interoperable and reusable data manage ICT data architecture manage ICT data classification manage intellectual property rights manage open publications manage personal professional development manage research data Marketing Analytics mathematical modelling MDX mentor individuals multidisciplinary research N1QL normalise data online analytical processing operate open source software perform data cleansing perform data mining perform project management perform scientific research promote open innovation in research promote the participation of citizens in scientific and research activities promote the transfer of knowledge publish academic research quantitative analysis query languages report analysis results Research Design resource description framework query language Scientific Computing scientific literature Social Network Analysis SPARQL speak different languages State Estimation statistical modeling techniques Statistics synthesise information teach in academic or vocational contexts think abstractly Unstructured Data use data processing techniques use databases use spreadsheets software visual presentation techniques write scientific publications XQuery

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