Data Scientist – Semiconductor Manufacturing (Richardson, Texas)

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Job Description

123-Sc Marketing

Description

Change the world. Love your job.
Texas Instruments is seeking experienced Data Scientist to join our team. Responsibilities include:

  • Enable everyday experimentation & insights extraction on petabytes of semiconductor manufacturing data (time series, images, audio, etc.)
  • Develop, refine, deploy, and support statistical and machine learning models utilizing state of the art approaches
  • Designs, develops, and programs methods, processes, and systems to consolidate and analyze unstructured, diverse big data sources to generate actionable insights and solutions for semiconductor manufacturing operations. Interacts across the organization 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
  • Create and utilize moderately complex algorithms and approaches, clean and synthesize training/test data, create/run simulations, and perform analysis of alternatives to best meet stakeholder requirements

Qualifications

Minimum requirements:

  • Bachelor’s degree in mathematics, statistics, engineering, a relevant technical field, or equivalent
  • 4 + years of work experience in analytics, data querying (SQL: PostgreSQL, MySQL, redshift, big query), data manipulation using distributed analytics and process technologies (Hadoop, Spark, Hive, MapReduce, Databricks), and scripting languages (Python, R, Julia)
  • Familiarity with statistics such as Bayesian, parametric, non-parametric, or experiment design
  • Solid understanding of software development concepts, principles, and theories such as object-oriented programming, functional programming, unit tests, test driven design, DRY, abstraction, modularity, clean interfaces, domain driven design, etc. 
  • Familiarity with common machine learning libraries for implementation such as sklearn, TensorFlow, torch, etc.

Preferred qualifications:

  • 2 years of work experience in solving problems using quantitative methodologies, data-driven projects from idea to full implementation (architectural design, experimentation, metrics definition, communicating progress, driving progress, etc.) 
  • Ability to establish strong relationships with key stakeholders critical to success, both internally and externally
  • Strong verbal and written communication skills
  • Ability to quickly ramp on new systems and processes
  • Demonstrated strong interpersonal, analytical and problem-solving skills
  • Ability to work in teams and collaborate effectively with people in different functions
  • Ability to take the initiative and drive for results
  • Strong time management skills that enable on-time project delivery
  • Experience building and evaluating ML models that operate on raw sensor data (detection, classification, tracking)
  • Experience building and evaluating ML models that operate on image data (detection, classification, tracking)
  • Familiarity with ML platforms such as data robot, dataiku, Alteryx

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