Construction Data Analyst

1 mese fa

Roma, Lazio, Italia Technip Energies A tempo pieno
About Us

At Technip Energies, we are a global and leading engineering and technology company, with a clear vision to accelerate the energy transition. We believe in a better tomorrow and strive to make tomorrow better. Our team of approximately 15,000 talented women and men is dedicated to designing and delivering added value energy solutions.

About the Role

We are currently seeking a Construction Data Scientist to join our Construction Data Science team based in Paris (France) and Rome (Italy). The successful candidate will report directly to the Global Construction Data Innovation Manager in Rome and will be responsible for developing and improving digital solutions, data science solutions (data analytics and AI), data accessibility, and bi reporting for better estimating, preparing, and controlling construction activities.

Key Responsibilities
  • Enable smarter business processes by using analytics for meaningful insights to help solve problems across various domains and industries.
  • Analyze data to identify patterns and trends to deliver recommendations for the future.
  • Develop data visualization and storytelling solutions.
  • Collaborate with businesses to understand their needs and identify use cases to develop.
  • Interact with Data Engineering to set up the data sources and all steps of dataset preparation.
  • Develop modelling methodology, features engineering, implement model, follow up model training and its validation, and definition of efficient model to deploy.
  • Monitor and fine-tune the model developed.
  • Deploy and industrialize data science and digital solutions developed.
  • Communicate findings to all stakeholders.
  • Prepare and deliver documentation, training, and webinar about data science.
  • Stay up to date with the latest advancements in AI and scripting language.
Requirements
  • Master's degree in Engineering (preference for IT and mechanical engineering), or Computer Science, or Mathematical.
  • Fluent in English.
  • Main Skills:
    • Analytical thinking for translating data into descriptive, predictive, and analytics and products.
    • Storytelling mindset.
    • Very good communication skills to identify the business requirements and to expose findings to all stakeholders.
    • Able to interface with IT and Data Office for understanding the data framework of data science projects.
    • Able to associate more efficient Machine Learning models to a specific business use case.
    • Able to identify algorithm metrics and monitoring system.
    • Data science curious, open mind, and updated to data science state of art.
    • Ability to think creatively and strategically with excellent problem-solving skills.
    • Able to manage more than one activity at the same time.
    • Attitude to perform the work in team, in an international and multi-cultural environment.
    • Ability to fulfill tasks on time with the required Company quality level.
    • Able to work and deliver in an incremental approach.
    • Availability to international mobility either for short- or long-term assignment.
  • Technical Competencies:
    • Knowledge of data mining, mathematics, and statistical analysis.
    • Knowledge of SQL (from a data scientist perspective, not necessarily dev or data engineering).
    • Knowledge of Scripting Language (., Python, R, Julia) and data science libraries.
    • Knowledge of main Machine Learning models (supervised and unsupervised).
    • Knowledge of data pipelines, cleansing, and data preparation.
    • Knowledge of Statistical computing package (., R) is a plus.
    • Knowledge of NLP, LLM is a plus.
    • Knowledge of Agile, Git, DevOps, and MLOps is a plus.
    • Knowledge of BI and visualization tools (., PowerBI) is a plus.
    • Knowledge of Dataiku and Synapse are a plus.
    Inclusion Standards

We adhere to four Inclusion Gold Standards: We challenge our biases and embrace diversity of thought; No one has all the knowledge and solutions, collectively we do; We foster a caring environment where people are respected, comfortable to share and be heard; We promote active listening for effective decision and action.

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