Mid Level Data Scientist - Machine Learning

at  PDF Solutions

OVERVIEW:

At PDF Solutions, we’re transforming the semiconductor and electronics manufacturing industry with our AI platform that improves yield and lowers manufacturing costs at some of the largest chip makers in the world. We’re seeking an experienced Data Scientist to join our team, who is responsible for developing pipelines to enable and drive production of the world’s most advanced chips. We look for people who are self-motivated and passionate about the transformative potential of AI. You’ll be able to hone your skills while working side by side with industry experts who have decades of experience. The candidate must be an organized and highly motivated team player with strong initiative and communication skills and possesses the drive to deliver quality results on time in a complex, intensive, and highly productive environment.

QUALIFICATIONS:

Master’s degree or higher in Computer Science, Computer Engineering, Electrical Engineering or similar discipline with industrial experience in software development
5+ years of experience with Python coding
5+ years of recent experience working as a Data Scientist in industry
Experience with Spark and PySpark
Experience with developing production-grade code, preferably in Python
Experience with data science and machine learning, including Python libraries such as NumPy, SciPy, Pandas and Scikit-learn
Strong professional written and verbal communication skills
Ability to pass a Data Science skills-based test
Experience with relational or NoSQL databases such as Oracle/Cassandra/Redis or similar
Ability to create model-ready data from raw data, at scale
Ability to translate business problems into data science pipelines
Pay Range: CAD $140,701.00 - CAD $165,531.00 /Yr

Research, design, implement, and validate ML Pipelines while collaborating with other data scientists.
Coordinate and collaborate with other Software Development groups so that ML Pipeline fits well with the rest of PDF Solutions’ software applications.
Balance adding new features with the need for stability and performance.
Grow development capabilities to align with the pace of business needs.