AI Data Scientist

Job summary

This role involves working as an Enterprise AI & Data Science Analyst within a multidisciplinary team focused on leveraging data and AI to address complex business challenges. The position emphasizes the development of analytical models and AI solutions to drive innovation across various industries.

Qualifications

• Bachelor's or Master's degree in Data Science, Computer Science, Artificial Intelligence, Statistics, Mathematics, Engineering, Physics, Economics, or a related field.
• Strong analytical and problem-solving abilities.
• Basic programming skills in Python, R, SQL, or similar technologies.
• Understanding of data analysis, statistics, and machine learning fundamentals.
• Effective communication skills for conveying technical findings to diverse audiences.
• Strong teamwork and collaboration capabilities.
• Fluency in English; knowledge of Nordic languages is a plus for local roles.

Responsibilities

• Assist in designing, developing, and deploying AI, machine learning, and analytics solutions.
• Analyze structured and unstructured data to derive business insights and opportunities.
• Support the creation of predictive models and data-driven solutions.
• Prepare, clean, and transform data for advanced analytics and AI applications.
• Evaluate and test AI models to ensure quality and performance.
• Collaborate with business stakeholders to translate requirements into analytical solutions.
• Develop dashboards, visualizations, and reports to effectively communicate insights.
• Work with AI, cloud, and data platforms to create scalable solutions.
• Stay informed about emerging trends in AI, Generative AI, machine learning, and data science.

Skills

• Experience with machine learning libraries such as Scikit-learn, TensorFlow, or PyTorch is advantageous.
• Familiarity with data visualization tools like Power BI, Tableau, or Plotly is a plus.
• Exposure to cloud platforms such as Azure, AWS, or Google Cloud is beneficial.
• Knowledge of Generative AI, Large Language Models (LLMs), or prompt engineering is a plus.
• Experience with SQL databases, data pipelines, or big data technologies is desirable.

Education

• Relevant academic background in data science, analytics, or related fields is required.

Tools

• Proficiency in programming languages such as Python, R, or SQL.
• Familiarity with machine learning and data visualization tools.