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Texas Instruments

Makes analog and embedded chips in its own plants

Data Scientist - Digital Experience Analytics

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeDallas, TX, USANo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field is required.
  • A cumulative GPA of at least 3.0/4.0 is required.

Responsibilities

  • Develop advanced machine learning models for personalization and customer journey optimization in a complex B2B business model.
  • Identify opportunities to use machine learning, artificial intelligence, and advanced analytics techniques to improve digital program design and effectiveness.
  • Partner with other data scientists to develop recommendation system components that predict relevant product and content messages for hundreds of thousands of users.
  • Create predictive models to segment, cluster, and label customer behavior, partnering with analysts to identify opportunities for targeted interventions.
  • Work closely with engineering teams to drive scalable, real-time implementations.
  • Collaborate with cross-functional teams to translate business requirements into data science solutions.
  • Partner with Digital Experience and user experience strategists to design and conduct A/B tests to optimize digital experiences and marketing campaigns.
  • Ensure data science best practices are followed and models are properly documented and version-controlled.
  • Stay current with advancements in data science and apply new techniques to improve analytics capabilities.

Desired Qualifications

  • A master's degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field.
  • Internship experience in data science or a related role, preferably in a sales, marketing, or e-commerce context.
  • Experience deploying models in production and adjusting models to improve performance.
  • Strong proficiency in Python or R for data analysis and machine learning.
  • Experience with machine learning libraries and tools such as scikit-learn, PyTorch, Kubeflow, and Streamlit.
  • Expertise in statistical analysis, experimental design, and causal inference.
  • Strong proficiency in SQL and experience working with large datasets.
  • Familiarity with cloud-based data science platforms such as Google Cloud Platform, Vertex AI, AWS, and Bedrock, and with Unix/Linux systems.
  • Innovator-level knowledge of developments in data science and adjacent fields, such as generative AI and human-in-the-loop workflows, and their application.
  • Experience with marketing automation and customer relationship management systems such as Salesforce, Marketo, and HubSpot.
  • Experience with graph databases such as Memgraph, Neo4j, and SpannerGraph.
  • Experience with customer data platforms such as Tealium, Segment, and ActionIQ.
  • Knowledge of client-side web analytics tools and techniques such as GA4, Adobe Analytics, and Fullstory.
  • Experience with natural language processing and text analytics.
  • Understanding of digital marketing concepts and customer journey mapping.

About the Company

Texas Instruments

Makes analog and embedded chips in its own plants

Texas Instruments designs and makes analog and embedded processing chips, the basic parts inside cars, factory equipment, data centers, and consumer electronics, and it sells one of the broadest chip catalogs in the industry. In 1958, its engineer Jack Kilby built the first integrated circuit, the building block of modern electronics, and later won a Nobel Prize for it. Its analog chips regulate power and convert signals such as sound and heat into data, while its microcontrollers act as small built-in computers, and TI earns money selling both to device makers. It also makes the graphing calculators many students use in math class. Texas Instruments was founded in 1930 and is based in Dallas, Texas.

Company size
10,001+
Company stage
IPO
Headquarters
Dallas, TX
Founded
1930

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