Sr. Software Development Engineer
AMD
Markham, Ontario, CA
1d ago

What you do at AMD changes everything

At AMD, we push the boundaries of what is possible. We believe in changing the world for the better by driving innovation in high-performance computing, graphics, and visualization technologies building blocks for gaming, immersive platforms, and the data center.

Developing great technology takes more than talent : it takes amazing people who understand collaboration, respect, and who will go the extra mile to achieve unthinkable results.

It takes people who have the passion and desire to disrupt the status quo, push boundaries, deliver innovation, and change the world.

If you have this type of passion, we invite you to take a look at the opportunities available to come join our team.

Machine Learning / Data Science Engineer

Come help us develop and finetune our product development and engineering pipeline solution that makes sure AMD's platforms crush the competition!

Our team writes large scale infrastructure software and tools using C#, Ruby and C++ for Windows and Linux environments.

Our software is utilized during all stages of product development across multiple AMD sites and includes distributed automation processes, web applications and databases to track millions of records generated by thousands of systems.

We are constantly adapting our software development processes to manage the challenges we accept.

Join us, if you are passionate about solving problems and working with the latest technologies, both hardware and software! We are looking for a Data Scientist who will support our engineering, validation, QA, release management and leadership teams with insights gained from analyzing data generated across the whole product development pipeline.

Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products.

Your Key Responsibilities

  • Work with stakeholders throughout the organization to identify opportunities for leveraging data to drive quality
  • Mine and analyze data from multiple data sources to drive optimization and improvement to product development, validation and release pipeline
  • Selecting features, building and optimizing classifiers using machine learning techniques
  • Assess the effectiveness and accuracy of new data sources and data gathering techniques
  • Develop custom data models and algorithms to apply to datasets
  • Use predictive modeling to increase and optimize customer experiences
  • Develop processes and tools to monitor and analyze model performance and data accuracy
  • Extending company’s data with third party sources of information when needed
  • Enhancing data collection procedures to include information that is relevant for building analytic systems
  • Processing, cleansing, and verifying the integrity of data used for analysis
  • Doing ad-hoc analysis and presenting results in a clear manner
  • Creating automated anomaly detection systems and constant tracking of its performance
  • Preferred Experience and Skills

    The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action.

    They must have strong experience using a variety of data mining / data analysis methods, using a variety of data tools, building and implementing models, using / creating algorithms and creating / running simulations.

    They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams.

    The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

  • Strong problem-solving skills with an emphasis on product development.
  • Good applied statistics skills, such as distributions, statistical testing, regression, etc.
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.
  • and experience with applications.

  • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
  • Experience querying databases and using statistical computer languages : R, Python, SLQ, etc.
  • Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc.
  • Experience with data visualization tools, such as D3.js, GGplot, etc.
  • Proficiency in using query languages such as SQL, Hive, Pig
  • Excellent written and verbal communication skills for coordinating across teams.
  • A drive to learn and master new technologies and techniques.
  • Qualifications

  • Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field
  • Must have 5-7 years of experience manipulating data sets and building statistical models
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