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Texas Instruments

Principal Data Scientist

Texas Instruments, Granite Heights, Wisconsin, United States

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Overview Change the world. Love your job. Texas Instruments is seeking experienced Data Scientist to join our team. As the Data Scientist in TI's Demand Analytics team, you will play a pivotal role in shaping and executing our demand planning and inventory buffer strategies for the company. You will be working side by side with a team of highly technical professionals that will consists of application developers, system architects, data scientists and data engineers. This role will be responsible for solving complex business problems through innovative solutions that deliver tangible business value. This position requires a technical leader with a strong technical background in AI/ML, simulation solutions, strategic thinking, and a passion for innovation through data. This team is responsible for: portfolio management for demand forecasting algorithms, generation of inventory buffer targets, segmentation of TI's products and simulation/validation frameworks, defining specs/reference architectures to best achieve business outcomes and ensuring security and interoperability between capabilities.

Responsibilities

Stakeholder engagement:

Work collaboratively and strategically with stakeholder groups to achieve TI business strategy and goals

Communicate complex technical concepts and influence final business outcomes with stakeholders effectively

Partner with cross-functional teams to identify and prioritize actionable, high-impact insights across a variety of core business areas

Technology and platforms:

Build simple, scalable and modular technology stacks using modern technologies and software engineering principles.

Simulate real world scenarios with various models and approaches to determine best fit of algorithms by varying the inputs across hundreds to thousands of variables

Research, experiment and implement new approaches and models that flex with the business strategy transformations

Lead data acquisition and engineering efforts

Develops and applies machine learning, AI and data engineering framework

Solutions, writes and debugs code for complex development projects

Oversees, evaluates and determines the best modeling techniques for various scenarios letting the data drive the conversation

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