Join Nokia as a Senior Data Scientist, where you'll leverage cutting-edge technologies to transform crude data into actionable insights. Your expertise in predictive analytics will drive impactful analyses, enabling data-driven decision-making across the organization. You will integrate and centralize diverse data sources while ensuring robust protection and accessibility for stakeholders. Collaborating closely with software engineering, you'll contribute specialized knowledge in big data processing. If you are passionate about data and innovation, and thrive in a dynamic environment, we invite you to shape the future of connectivity with us.

Education:

PhD in Statistics, Machine Learning, Data Science, Computer Science, or Computer Engineering (MSc may be considered).

Experience:

5–6 years of significant professional experience in Data Science.

Expertise in Machine Learning:

Proficient in both supervised and unsupervised learning.Techniques: Linear and logistic regressions, random forests, gradient boosting, neural networks (RNN, LSTM, CNN), text mining, topic extraction, NLP, K-Means, decision trees.Applications: Computer vision, Generative AI, Language Models (e.g., GPT), Retrieval-Augmented Generation (RAG).

Technical Skills:

Deep knowledge of Python (including libraries such as scikit-learn, Pandas, NumPy).Experience with Jupyter, Spark/Scala or R, PostgreSQL, and ELK stack.Proficiency in Java, Kubernetes, Docker, and microservices-oriented architecture.Familiarity with MLOps practices and collaborative tools (e.g., GitLab).

Language Skills:

English fluency (both written and verbal) is mandatory.Technical Leadership: Drive and manage projects, activities, and technical responsibilities within your area of expertise, ensuring high-quality deliverables and documentation.Innovation & Development: Develop tools, methods, and processes; write requirements and specifications to guide R&D efforts.Collaboration & Support: Partner with internal and external teams, providing training, consulting, and technical support to Product Management, Customer Interface, and business lines.Problem-Solving & Efficiency: Lead serious issue resolution, seek cost-efficient solutions, and foster change in the environment.Predictive Analysis: Apply deep expertise in predictive analytics to deliver insights and solutions.Planning & Organization: Contribute to resource planning, work estimation, and process optimization.