Job ID
484271
Posted since
07-Nov-2025
Organization
Global Business Services
Field of work
Information Technology
Company
Siemens S.A.
Experience level
Experienced Professional
Job type
Full-time
Work mode
Hybrid (Remote/Office)
Employment type
Permanent
Location(s)
* Amadora - Lisboa - Portugal
Siemens Global Business Services (GBS) enables Siemens units worldwide and external customers to accelerate their business transformation into a sustainable and digital future.
Our portfolio comprises services driven by expertise and the latest technology – with a strong focus on innovation and digitalization in areas like business administration, human resources, supply chain management, sales, marketing, and engineering.
In our GBS Western Europe and Africa Hub we are already more than 1400 connected people, from over 57 different nationalities spread across 14 countries.
GBS Digital Solutions offer innovative technology solutions and customer-oriented digitalization services and co-develop digital solutions to solve our customers business challenges, leveraging our modern technology layer and partner ecosystem. We consult them with our holistic, 360° digital advisory service, encompassing the data-driven discovery of digitalization potential along their business processes.
Want to know more about GBS? Check out here
Are you ready to be part of the change and help us make real what matters?
Your mission will be…
* Collaborate with our teams in data science projects running at Siemens, with a focus on AI/LLM powered solutions that generate positive impacts for thousands of people and processes worldwide.
* You will be involved in running and improving data science endeavors, focusing on NLP, LLM modelling, Exploratory Data Analysis, conducting statistical analyses to understand data characteristics, Feature Engineering, Model Development and Evaluation, Model Deployment and Monitoring, as well as improving and retraining models to improve performance.
We are looking for someone with…
* Higher education in a STEM related field, with major statistics or mathematics components.
* Five to ten years of experience in Data Science / ML projects.
* Professional experience in end-to-end data science / machine learning initiatives, encompassing data understanding, preparation, modelling and evaluation, and deployment.
* Solid command of data science concepts and principles - especially around EDA, modelling and evaluation - is mandatory.
* Fluency in English, written and spoken, is mandatory.
* Professional experience with Python and industry standard Python data science / ML frameworks (e.g. scikit, pytorch, keras, opencv, pandas, others) is mandatory.
* Professional experience in data preparation/transformation (e.g. SQL, pandas) is mandatory.
* Professional experience in NLP is mandatory.
* Professional experience working in ML with AWS or Azure is mandatory, AWS highly preferred.
* Experience with LLM, RAG, and Generative AI technologies is highly valued.
What you can expect from us…
A hybrid and flexible working model to promote a better work-life balance, along with a budget for home office support and the opportunity to do 16 hours a year of volunteer work. A health insurance, access to our on-site medical center, plus the chance to join sports groups.
In addition, you'll have access to online learning platforms and discounts with our partners. A shuttle bus to commute to the facilities and the possibility of financial support to your studies.
What makes us proud as an employer:
* Merco – Companies and Leaders with the Best Reputation in Portugal (#1 Technology/Manufacturing)
* Forbes – World's Best Employers (#1 Engineering & Manufacturing)
* LinkedIn – LinkedIn Top Companies (#2)
* OnStrategy – REPSCORE 2024: Brands' Reputation in Portugal (#1 Engineering & Electronic Services)
* Fortune – World's Most Admired Companies (#1 Industrial Machinery)
* SSON – Top 20 most admired Shared Services Organizations and Global Business Services in 2024
Please attach your CV in English.
#Siemens #PeopleAtSiemens #GBSpartnerofchoice
Siemens is committed to creating a diverse environment and is glad to be an equal opportunity employer. We strongly encourage applications from a diverse talent pool