Our vision is to transform how the world uses information to enrich life. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing.
Responsibilities Include, But Not Limited To
- Strong desire to grow a career as a Data Scientist in highly automated industrial manufacturing doing analysis and machine learning on terabytes and petabytes of diverse datasets.
- Experience in the areas: statistical modeling, feature extraction and analysis, supervised/unsupervised/semi-supervised learning. Exposure to the semiconductor industry is a plus but not a requirement.
- Ability to extract data from different databases via SQL and other query languages and applying data cleansing, outlier identification, and missing data techniques.
- Strong software development skills.
- Strong verbal and written communication skills.
- Experience with or desire to learn:
- Machine learning and other advanced analytical methods
- Fluency in Python and/or R
- pySpark and/or SparkR and/or SparklyR
- Hadoop (Hive, Spark, HBase)
- Teradata and/or another SQL databases
- Tensorflow, and/or other statistical software including scripting capability for automating analyses
- SSIS, ETL
- Experience working with time-series data, images, semi-supervised learning, and data with frequently changing distributions is a plus
- Experience working with Manufacturing Execution Systems (MES) is a plus
- Existing papers from CVPR, NIPS, ICML, KDD, and other key conferences are plus, but this is not a research position
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement. Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.