Senior Data Scientist

NOTE: This is a fully remote position that is open to both the US and Canada

Today’s world depends on semiconductor chips. They are the brains of your smartphone, automobile, and the internet. Tignis is the leading software company that delivers cutting-edge AI/ML products that optimize and control the manufacturing processes for those chips. Through the use of our products and solutions, semiconductor companies can build more powerful chips faster with higher quality and less waste.

Tignis is a 100% remote-work company headquartered in Seattle, WA. We have assembled an experienced and talented team that spans physical science (materials science, physics, chemical engineering, and mechanical engineering), software engineering, and artificial intelligence. If you want to become a member of a business-savvy and customer obsessed team delivering extraordinary AI/ML solutions for the most advanced manufacturing organizations around the globe, join us at Tignis!

This role can be based anywhere in the US or Canada.

The Role:

We are looking for an experienced Data Scientist to help us develop AI process control solutions that enable never-before-possible use cases in semiconductor manufacturing. This is not a typical data science position - you must be ready to look behind simple ML approaches to identify solutions to complex problems. Common solutions involve combining ML models, physical models, and optimization strategies to solve an “inverse problem” (choose the process inputs X to achieve the desired outcome Y). You must be naturally curious and detail-oriented to be successful. You will both have the chance to contribute to the core software product and work directly with customers.

This role is permanently remote and does not report to an office.

Responsibilities:

• Discover solutions to previously unsolved problems at the interface of data science, physics, and process control.
• Work with customers on their engineering challenges and design analytical solutions that combine the best in engineering, simulation, and machine learning.
• Use statistics and data science to make decisions based on data.
• Create machine learning models that can be deployed to production in semiconductor manufacturing.
• Work with internal software engineering teams to help design software libraries that accelerate reusable machine learning.
• Communicate results to a broad range of external and internal constituents, from engineer to CEO.
• Stay up to date with the latest in machine learning developments.
• Collaborate across disciplines to deliver an amazing customer experience.

Requirements:

• Strong technical background in math, statistics, programming, and machine learning. This could be demonstrated through a PhD in an aligned quantitative field or alternative combinations of education and experience.
• Familiarity with software engineering concepts, including git version control and scripting with python
• Knowledge of machine learning fundamentals and methods, with a proven ability to apply them effectively to solve real-world data science problems

Preferred Qualifications:

• 3+ years of experience applying data science toolkit to solve challenging technical problems in a business/industrial setting
• Working knowledge of deep learning frameworks and an ability to implement and debug custom model architectures (TensorFlow preferred)
• Comfortable with scientific programming concepts: using scipy modules with ease, fitting experimental data to parameterized physical models, debugging optimization issues, etc.

We offer a comprehensive benefits package including medical, dental, and vision insurance, 401(k) contributions, UTO, and much more.

We appreciate all applications, but only selected candidates will be contacted for an interview.