기본

Data Scientist - Growth & Revenue Analytics

milano, lombardia, Italy 회사: JR Italy 클라이언트 / 고용주: Mollie
게시됨: 19.05.2026
마감일: 03.07.2026
직무 추천서: ac8aaa8dd4a7e4ac25e266b3648a1086

직무 정보

위치
milano, lombardia, Italy
회사
JR Italy
클라이언트 / 고용주
Mollie
직무 추천서
ac8aaa8dd4a7e4ac25e266b3648a1086
목록 유형
기본
EU 취업 허가 필요
아니
게시됨
19.05.2026
마감일
03.07.2026

직무 설명

A leading fintech company in Milan is seeking a Data Scientist to join their Revenue Operations Domain. You will develop predictive models and translate complex data into actionable strategies, directly impacting business decisions. The ideal candidate has over 3 years of experience in Data Science, strong Python and SQL skills, and the ability to clearly communicate insights. Join a fast-growing team focused on improving customer acquisition and retention using advanced analytics and machine learning. #J-18808-Ljbffr

기술

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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