Data Scientist

Bombardier

Bombardier, a leader in aircraft design and maintenance, offers the opportunity to work with cutting-edge technology in the aerospace sector. The role of a Data Scientist is crucial in developing innovative models and integrating AI into applications to enhance product quality and user experience. Bombardier values continuous employee development, providing an environment where individuals can fully realize their potential.

In this role you can expect to have the responsibilities:

• Design and develop AI and machine learning models using Azure Databricks.
• Create models to address business needs through predictive, prescriptive, and descriptive analytics.
• Deploy and manage models in production environments using Azure tools.
• Collaborate with data engineering to prepare datasets for model development.
• Integrate AI models into applications with developers' support.
• Conduct experiments for model performance optimization and algorithm efficiency.
• Track model versions and performance using Azure tools.
• Document development processes and share insights with stakeholders.

This role comes with the following benefits:

• Dental, medical, life, and disability insurance plans.
• Competitive base salary.
• Retirement savings plan.
• Employee Assistance Program.
• Tele Health Program.

This role requires you to have:

• Bachelor's or Master's in Data Science, Machine Learning, Computer Science, or related field.
• 5+ years experience in data science and machine learning.
• Experience with Azure Databricks, including model registry and data catalog.
• Proficiency in Python, SQL, and Spark.
• Strong knowledge of machine learning algorithms and statistical methods.

You would benefit from having:

• PhD in a relevant field.
• Experience with CI/CD workflows for AI/ML.
• Hands-on experience with TensorFlow, PyTorch, or scikit-learn.
• Familiarity with Azure ML and other Azure ecosystem tools.
• Interest in AI/ML advancements and innovation.

Bombardier is an equal opportunity employer, encouraging applicants from diverse backgrounds to apply, including those with legally protected characteristics.