WerkstudentEnglisch & Deutsch
Werkstudent (m/w/d) Data Scientist
Jetzt bewerben
Vor Ort
Englisch & Deutsch
Erforderliche Skills
AzureAWSLLMpandasIBM CloudPythonSciPySparkPyTorchscikit-learnNLPSQLGenAI
Stellenbeschreibung
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 our clients locally based skills and technical expertise to drive innovation and adoption of new technology.
Your Role And Responsibilities
During your internship, you can enhance your knowledge and gain professional experience by working on client projects. This role provides an exceptional opportunity to build a compelling portfolio, acquire new skills, gain insights into diverse industries, and embrace novel challenges for your future career.
At IBM, we prioritize continuous learning, skill development, and personal growth within a culture of coaching and mentorship. As an intern, you'll experience this culture and have the opportunity to advance to our associate program based on results and performance.
Work Experiences You Could Be Exposed To
Mentored Analytical Support: Receive mentorship from diverse professionals in science engineering and consulting applying 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: Utilize program 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.
Preferred Education
Bachelor's Degree
Required Technical And Professional Expertise
Currently pursuing a quantitative degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.
Strong Interpersonal skills that enhance collaboration and relationship building, while also managing dynamic workloads in an agile environment.
Have initiative and passion to actively seek new knowledge and improve skills while embracing a growth mindset to assimilate diverse viewpoints.
Demonstrate leadership experience and ability to communicate effectively through active listening; while also be willing to adapt and have a readiness to take ownership of tasks and challenges.
Familiarity with one or more scripting languages (Python preferred), or a proven computer science foundation.
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 (e.g., 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.
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 our clients locally based skills and technical expertise to drive innovation and adoption of new technology.
Your Role And Responsibilities
During your internship, you can enhance your knowledge and gain professional experience by working on client projects. This role provides an exceptional opportunity to build a compelling portfolio, acquire new skills, gain insights into diverse industries, and embrace novel challenges for your future career.
At IBM, we prioritize continuous learning, skill development, and personal growth within a culture of coaching and mentorship. As an intern, you'll experience this culture and have the opportunity to advance to our associate program based on results and performance.
Work Experiences You Could Be Exposed To
Mentored Analytical Support: Receive mentorship from diverse professionals in science engineering and consulting applying 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: Utilize program 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.
Preferred Education
Bachelor's Degree
Required Technical And Professional Expertise
Currently pursuing a quantitative degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.
Strong Interpersonal skills that enhance collaboration and relationship building, while also managing dynamic workloads in an agile environment.
Have initiative and passion to actively seek new knowledge and improve skills while embracing a growth mindset to assimilate diverse viewpoints.
Demonstrate leadership experience and ability to communicate effectively through active listening; while also be willing to adapt and have a readiness to take ownership of tasks and challenges.
Familiarity with one or more scripting languages (Python preferred), or a proven computer science foundation.
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 (e.g., 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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