At Boeing, we innovate and collaborate to make the world a better place. We’re committed to fostering an environment for every teammate that’s welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us.
Boeing Vancouver is seeking a Lead Data Scientist - NLP to join our team. The position will be based from our Richmond, British Columbia office, and a hybrid work style is offered.
As a Data Scientist in Boeing Digital Services, you will empower Boeing’s customer-facing software tools, products and services with cutting-edge analytics technologies. You will apply your rich NLP expertise to the unique challenges of aviation and aerospace and will bring your data science specialty to cross-functional software and engineering teams to help develop, launch and maintain leading-edge operational solutions around the world. You will work closely with customers and product teams, developing understanding of their problems, priorities and business needs.
In this position you will lead quality and skills-enhancement initiatives and champion a learning culture that values curiosity and self-betterment. You will mentor and coach data scientists in their careers, and champion major improvement and growth initiatives as you envision them. Embedded within a large product development collaboration, this role will require strong software development understanding in addition to traditional data science expertise, and a strong customer focus.
This role will be part of the Boeing Digital Services Data Science team. Depending on need and fit, the role will support multiple products and services in the Digital Tech Ops and Defence Analytics domain, serving both the commercial and military aviation markets.
Boeing Vancouver houses an eclectic group of passionate data scientists who help customers by making sense of big, complex systems in the world of aviation. We combine deep scientific thinking, mathematical prowess and analytics technology with creativity and detective work to uncover rare insights hidden within data. We harness practical knowledge of engineering, business, and aviation to build both internal and external, customer-facing solutions. Together, we deliver insights that change the world on the ground and in the air.

BASIC QUALIFICATIONS (REQUIRED SKILLS/EXPERIENCE):

• 5+ years’ experience working as part of an integrated data science development team.
• Demonstrated expertise in applied Natural Language Processing.
• 3+ years of experience with Python.
• 3+ years of experience with data querying (e.g. SQL).
• Experience writing code in a collaborative environment (e.g. using Git).
• Candidate must be eligible for authorization under the Canadian Government Controlled Goods Program (CGP).
• Must be able to obtain Canadian Secret Level II Security Clearance.
• Must be legally able to work in Canada.
• Individual must not pose a risk for safeguarding of controlled goods.
• Must be eligible to handle US export-controlled data.

PREFERRED QUALIFICATIONS (DESIRED SKILLS/EXPERIENCE):

• Domain knowledge of the aviation & aerospace industry.
• Experience in application and evaluation of generative large language models.
• Expertise in one or more of the following technologies:
• Deep learning tools (e.g. TensorFlow, PyTorch, Keras, MLlib).
• MLOps and CI/CD techniques and tools (e.g. GitLab CI, MLflow, TFX).
• Large-scale data analysis technologies (e.g. Spark, Databricks, Delta).
• Cloud technologies (e.g., Azure, Google Cloud).
• Experience in production data and modeling pipeline development.
• Experience in production analytics services deployment.
• Experience presenting to non-technical audiences.
• Project management experience (Agile, Kanban).
• Expertise in Predictive Maintenance.

• Communicates with customers, product owners and other stakeholders to understand requirements, steer development efforts and communicate deliverables/results.
• Leads cross-functional teams that determine, define and deploy highly complex NLP solutions to meet business objectives of engineering and maintenance stakeholders.
• Provides hands-on technical leadership in machine learning and analytics, with a special emphasis on NLP, ML Ops and cloud-deployed data services.
• Develops production-level analytics tools for internal and customer-facing applications.
• Oversees technical approach, evaluation, validation and continuous performance monitoring of supported applications, models and analyses.
• Leads setup of data and modeling pipelines.
• Champions culture of quality, learning, trust, and collaboration.