Posted:
9/2/2024, 6:20:41 PM
Location(s):
Milan, Lombardy, Italy ⋅ Lombardy, Italy
Experience Level(s):
Junior ⋅ Mid Level
Field(s):
Data & Analytics
Workplace Type:
Hybrid
Data Scientist/Statistician
Location: Milan, hybrid
Job Overview
Member of the European Data Science & Advanced Analytics team. Under some guidance, he/she will execute and provide expertise in developing and applying statistical methodologies and analyses to support set-up, implementation and maintenance of solutions for EMEA countries with focus on Italy & Greece.
Principal accountabilities are:
• Collaboration in projects of the European Data Science & Advanced Analytics Team
• Support in development and deployment of new product offerings.
• Ongoing development and improvement of quality control methodologies (e.g., anomaly detection, isolation trees), ML based imputation approaches and various projection methodologies (e.g., geo-spatial, cloning, ML based, etc) specifically for large data sets.
• Support in the implementation and deployment of new statistical and machine learning solutions on big data platforms, in collaboration with technology teams.
• Use scientific methods, algorithms and processes to extract knowledge and insights from structured and unstructured data
• Apply statistical approach and appropriate methodology to meet insight needs, including preparing/analyzing data, developing and programming; conducting statistical analyses to derive conclusions from the studies, assisting or directly preparing presentations of results.
• Design and execute quantitative and qualitative analysis in collaboration with BU engagement manager and country local offices.
• Member of project team ensuring efficient and effective project delivery to meet project team and client expectations
Our ideal candidate will have:
• Master degree in Statistics, Mathematics, Economics/Econometrics or related fields with a strong focus on quantitative analysis, including an acceptable number of courses in statistical methods and theory.
• At least 3 years of professional experience in data science/quantitative data analyses or PhD with at least 1 year of relevant professional experience. Ideally with market research or health and life sciences project experience
• Very good knowledge of the higher statistical (incl. Sampling) and econometric methods in theory and practice.
• In-depth understanding of machine learning and statical models
• Some experience in developing and deploying scalable solutions in the cloud (for example using Azure, AWS, Hadoop etc)
• Strong programming skills and hands on experience on Python and SQL
• Good knowledge of other sw like Git and MS Office (especially presentation capabilities with PowerPoint and ability to create and manipulate data via Excel)
• Excellent analytic mindset and logical thinking capability, strong QC mindset, attention to details capabilities
• Passion and curiosity about the data and their analyses.
• Commitment to working independently and collaboratively with others in and across Team and Organization to accomplish shared goal
• Proven time management and personal organizational skills; ability to manage multiple projects and deliver high quality work within timeline
• Good communication and presentation skills with focus on the technical aspects of a project and the ability to develop usable documentation.
• The desire to learn, interest in the healthcare / life sciences and commitment to a rapid development curve
• Fluent in Italian and English
IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com
Website: https://iqvia.com/
Headquarter Location: Danbury, Connecticut, United States
Employee Count: 10001+
Year Founded: 1982
IPO Status: Public
Last Funding Type: Post-IPO Debt
Industries: Analytics ⋅ Health Care ⋅ Life Science