AI & Data Analyst

Role overview

Key responsibilities

• Collect, clean, validate, and analyze structured and unstructured data from multiple sources.
• Develop and maintain dashboards, reports, and KPIs using Power BI or similar BI tools.
• Design, build, and deploy AI and machine-learning models; perform predictive, prescriptive, and statistical analysis.
• Automate data processing with Python, SQL, and analytics tools; develop and optimize data models, pipelines, and ETL processes.
• Collaborate with stakeholders to translate business needs into analytical solutions and support generative AI and automation initiatives.
• Maintain data quality, governance, security, and compliance; prepare technical documentation, presentations, and management recommendations.

Qualifications and experience

• A bachelor's degree in a related field is listed; a later candidate-information section also says bachelor's degree or diploma.
• Requires 3–6 years in data analytics, business intelligence, artificial intelligence, or machine learning.
• Requires hands-on experience with Python, SQL, and Power BI, Tableau, or similar analytics tools.
• Requires experience with Scikit-learn, TensorFlow, PyTorch, or similar machine-learning frameworks and developing predictive models, dashboards, and data visualizations.
• Knowledge of Azure, AWS, or GCP AI platforms is preferred.

Technical skills

• Skills listed include Python, SQL, Power BI, Tableau, machine learning, predictive analytics, generative AI tools, data modeling, data warehousing, ETL development, and statistical analysis.
• R, Azure AI, Azure Machine Learning, and AWS SageMaker are listed as preferred.
• AI, machine-learning, data-analytics, cloud-AI, or Google Data Analytics certifications are an advantage.
• English proficiency is requested; the description gives basic, professional, and fluent as options.

About Technip Energies

Application process

• The recruiting team screens applications for skills, experience, and team fit.