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ANALYST –LARGE LANGUAGE MODEL ENGINEER

Descrição da oferta de emprego

Analyst – Large Language Model Engineer Location.
Lisbon, Portugal/Athens, Greece/Sofia, Bulgaria Work Model.
Hybrid or Office based Join the Methods and Evidence Generation (MEG) Team to help us deliver high quality scientific research to our clients in the global pharmaceutical and healthcare industries.
You’ll be working in a global company of over employees in more than 100 countries, with a broad range of healthcare information, technology and service offerings.
Our goal is to contribute to the body of scientific evidence that allows medical practitioners to treat patients in the most effective way, and health systems to include as many patients as possible.
We use data, collected for clinical (and other) purposes to answer research questions such as \"which treatment works best in the real world, beyond the clinical trial setting?\" Our fast paced and supportive environment attracts individuals who care deeply about the quality, timeliness and subsequent impact of their work; who thrive when exposed to the scale and variety of scientific challenges we face.
Your primary responsibilities as a LLM Engineer in our team will be wide ranging, but may involve.
Contributing to improving operational efficiencies of workflows, including the use of large language models Applying and testing various LLM methods (prompt engineering, RAG, etc.) Integrating LLMs into standalone applications and workflows Contribute to simple Python applications development Conduct statistical analysis and develop machine learning models on real-world databases as specified in the protocol Assist in the preparation of abstracts, manuscripts and/or presentations to conferences Requirements MSc or equivalent in a STEM subject (i.
.
computer science, engineering, statistics, maths, physics) or in a related discipline Strong programming skills in Python (R could also be considered) Excellent time management skills, contributing to multiple projects with competing timelines Commitment to working collaboratively and effectively with people of other disciplines Strong written and verbal communication skills Fluency in English (spoken and written) - – please submit your CV in English Eligibility to work without visa sponsorship Preferred Qualities Experience in Python and/or R Experience in using large language models and/or machine learning models to solve business problems Experience with open source large language models Experience with Shiny, Streamlit, Django or similar framework Experience with healthcare data Interpersonal, teamwork and communication skills JOIN US You will have the opportunity to play an important part in helping our clients drive healthcare forward and ultimately, improve outcomes for patients.
Whatever your career goals, we are here to ensure you get there! IQVIA is a leading global provider of advanced analytics, technology solutions and clinical research services to the life sciences industry.
We believe in pushing the boundaries of human science and data science to make the biggest impact possible – to help our customers create a healthier world.
Learn more at https://jobs.
qvia.
om IQVIA is a world leader in using data, technology, advanced analytics, and expertise to help customers drive healthcare – and human health – forward.
Together with the companies we serve, we are enabling a more modern, more effective and more efficient healthcare system, and creating breakthrough solutions that transform business and patient outcomes.
To get there, it takes diverse skills and a curiosity to explore new possibilities.
No matter your role, everyone at IQVIA, including our colleagues at Q² Solutions, contributes to our shared goal of improving human health.
Thank you for your interest in growing your career with us.
Ir à oferta completa

Detalhes da oferta

Empresa
  • IMSH Tech Sol Portugal LD (PT71)
Localidade
  • Em todo Portugal
Endereço
  • Indeterminado - Indeterminado
Tipo de Contrato
  • Indeterminado
Data de publicação
  • 09/05/2024
Data de expiração
  • 07/08/2024
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