Introduction
In this role, you’ll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer local skills to drive innovation and adoption of new technology.
Career and Master's Degree?
At IBM CIC, you can combine a promising work environment for the start of your career with a part‑time master’s course at a renowned university of your choice.
Master Internship@IBM CIC
Within the scope of the 2–3 year Master Internship@IBM CIC program, you will gain professional experience in consulting while completing your master's study. The duration of studies depends on the university and is between two and three years. The work volume allows you to focus on your master’s degree while you will also experience challenging assignments, a team‑oriented dynamic environment, and active co‑determination. You will write your master’s thesis in collaboration with your department.
Your Role And Responsibilities
Account And Project Support Activities
Assisting the lifesciences industry leader in Switzerland
Collating and updating IBM offerings around AI adoption and aligning them to client needs
Creating presentations to position IBM in client meetings
Planning and preparation of client meetings, events and workshops
Supporting business‑development activities and internal reporting on opportunities
Business Development Activities
Development of response material for proposals
Supporting team coordination and internal processes on sales bids
Assisting in material creation for oral presentation sessions
Producing reports for sales and delivery cadence calls
This position will be based within the Hybrid Cloud & Data service line
Additionally, Your Work Experience Could Be Exposed To
Mentored analytical support: receive mentorship from diverse professionals in science, engineering and consulting to apply analytical rigor and statistical methods to predict behaviors
Data integrations: develop skills in writing efficient and reusable programs to cleanse, integrate and model data; evaluate model results contributing to data‑driven insights
Effective communication: assist in conveying analytical results to both technical and non‑technical audiences, refining your ability to communicate complex findings
Tech‑driven data transformer: use programming languages like Python to build data pipelines, extracting and transforming data from repositories to consumers. Gain exposure to cloud platforms, ETL tools and data integration, expanding your tech toolkit
Eligibility
This job is only for candidates who will have finished their bachelor studies by September 2026 (or earlier) and plan to start with a master’s degree in autumn or in winter 2026 (Swiss university/university of applied sciences, study course of your choice).
Required Technical And Professional Expertise
Currently pursuing a quantitative degree in Computer Science, Statistics, Mathematics, Engineering, or a related field
Strong analytical and problem‑solving skills, with the ability to work with complex datasets and extract meaningful insights in a life‑sciences context
Familiarity with one or more scripting languages (Python preferred), or a proven computer‑science foundation
Understanding of or strong interest in life sciences, healthcare systems, or pharmaceutical research, with the ability to connect data insights to real‑world applications
Strong interpersonal and communication skills, enabling effective collaboration with both technical and non‑technical stakeholders
Proactive mindset with the ability to take ownership of tasks, adapt to new challenges, and work in an agile, interdisciplinary environment
Curiosity and willingness to continuously learn new technologies, methods, and domain knowledge in both data science and life sciences
Fluent in English and German – at least C1 level (written and spoken)
Swiss / EU nationality or a valid Swiss work permit
Preferred Technical And Professional Experience
Demonstrate familiarity or interest in statistical analysis or data mining through previous internships, personal/academic projects, hackathons, and/or publications
General familiarity with databases, data‑engineering tools (SQL, Spark) and cloud platforms (IBM Cloud, Azure, AWS). Experience with NLP/LLM/GenAI is a plus
Experience using machine‑learning/data‑science libraries in Python (scikit‑learn, SciPy, pandas, PyTorch) is a plus
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