Job Description

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.

A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe.

You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio.

Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.

Your Role And Responsibilities

IBM Baltic Client Innovation Centre in Lithuania is hiring Data Science/Developer interns. Candidates must have interest & experience in one or more areas relevant to the knowledge engineering life cycle such as natural language processing, Large language models, information integration, entity resolution, machine learning, ontologies, large-scale data management, development of statistical models. In this role you will get an opportunity to learn and work on real projects with some of the best professionals in the market.

Required Technical And Professional Expertise

Education in a quantitative field (e.g., Computer Science, Engineering, Mathematics, Statistics, Operations Research, Physics or other natural sciences)

Fluent English.
Good Python programming skills are a must.
Coursework in mathematics, statistics, machine learning, and data mining, feature engineering
High level of comfort with various data types and structures: structured versus unstructured data
Experience in data cleaning, validation, integration
Good understanding of multivariate statistical and machine learning algorithms, such as principal component analysis, neural networks, discriminant analysis, linear and logistic regression, k-nearest neighbors, classification and regression tree, etc.

Toolbox: Jupyter Notebooks, Ollama, Pandas, Scikit-learn, Matplotlib, Github, TensorFlow, Flask/FastAPI, Langchain/Langraph, ChromaDB/FAISS.

Preferred Technical And Professional Experience