Jobs in the United States

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Added 2 mins ago
Senior Bioinformatician
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The Senior Bioinformatician serves as the bioinformatics lead within the Infectious Diseases Unit at the NC State Laboratory of Public Health, supporting sequencing and…
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FP&A Analyst
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Lead budgeting, forecasting, long-range planning, and financial performance analysis.
Added 3 mins ago
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Infrastructure/System Administrator Lead
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- $123,400 to $178,500 USD / year
…portfolio.As a Senior Data Scientist on the AI Delivery Team, you will lead the design and delivery of end-to-end AI and machine learning solutions that span programs and products - setting…
Added 4 mins ago
Infrastucture Engineer - TS/SCI with Polygraph
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The Infrastructure DevOps Lead will manage the design and implementation of complex cloud infrastructure and DevOps solutions. In addition to being a hands-on technical leader with…
Added 5 mins ago
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Okta Engineer, Senior Consultant
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- $113,000 to $188,000 USD / year
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Added 5 mins ago
Security Engineer - Federal Customer
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· Collaboration: Ability to work effectively in a team environment and lead technical initiatives.
Added 5 mins ago
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Staff Software Engineer - Card Technology
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Forward Deployed Engineer, AWS Forward Deployed Engineering, US Government
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Background as a founder, engineering lead, or startup builder with high ownership and urgency
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Forward Deployed Engineering Manager, AWS Forward Deployed Engineering
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Amazon Leo Network Development Engineer, Leo Enterprise Network Infrastructure
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Data Scientist Specialist
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…agents. Our team develops analytical products that facilitate lead generation and provide critical insights for audit and investigative activities. Our methods frequently involve statistics…
Added 5 mins ago
Data Scientist Specialist
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Capital One Shopping Tech, Full - stack Engineer 5 (Remote - Eligible)
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Added 5 mins ago
Full-stack Engineer 5 (Python, AWS, Typescript)
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Added 5 mins ago
Sr. Manager, Security Engineer
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Added 5 mins ago
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Texas Instruments

Data Scientist (Manufacturing/Facilities)

Dallas, TX, United States
Richardson, TX, United States

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Job details

Experience: 5+ years of experience as a Data Scientist working with time series and time studies data within the semiconductor, manufacturing, or facilities domain
Posting language: English
Posted: Oct 29, 2026

Original job description

About This Role Smart Manufacturing and Automation (SMA) at Texas Instruments is looking for a Sr./Lead Data Scientist who can fundamentally change how facilities operations leverage data. This role sits at the intersection of deep time series expertise and enterprise-scale AI deployment . You will work directly with operational teams to extract signal from complex sensor, equipment, and process data, build production-grade anomaly detection and forecasting systems, and drive the adoption of Agentic AI solutions across a global organization spanning semiconductor manufacturing, facilities operations, and engineering. This role is not about building models in isolation. It involves solving problems in complex operational environments, earning the trust of domain experts, and deploying intelligent systems that scale. About You You are an experienced data scientist energized by ambiguous, high-stakes problems. You can walk into a room with facilities engineers and operations specialists, ask the right questions, and leave with a clear picture of what needs to be modeled. You do not just build models - you understand the operational problem deeply enough to know when a simpler statistical approach beats a complex neural network. You are self-directed. You find anomaly patterns others miss, propose forecasting solutions before anyone asks, and take ownership of outcomes from data exploration through production deployment. You stay current with emerging technologies - including agentic AI frameworks and large language model tooling - not because it is trendy, but because you know how to apply them where they genuinely move the needle in a manufacturing environment. What You'll Do Analyze and Model Time Series Data

Engage directly with operational and engineering stakeholders to understand, map, and extract value from complex time series data - translating domain expertise into reliable, production-grade models
Develop and deploy anomaly detection, predictive maintenance, and forecasting models against equipment sensor data, facility operations data, and manufacturing process signals
Design and implement end-to-end ML pipelines that reduce manual analysis effort and increase operational decision quality at scale

Build with Engineering Excellence

Build scalable, maintainable data science solutions with clean architecture, disciplined testing, and rigorous version control practices
Design and deploy Agentic AI solutions leveraging emerging frameworks such as Model Context Protocol (MCP) and agent-to-agent (A2A) protocols to create intelligent, composable data analysis workflows
Apply strong ML engineering fundamentals to ensure models are robust, extensible, and production-grade across distributed manufacturing environments

Lead and Elevate

Define and drive technical strategy for time series analytics and enterprise AI deployment - setting standards and identifying platform-level opportunities that compound impact over time
Lead enterprise-wide Agentic AI initiatives from proof of concept through scaled production deployment across TI's global manufacturing and facilities organization
Mentor data scientists and engineers, elevating team capability through technical guidance, model reviews, and knowledge sharing
Proactively identify and self-initiate improvements beyond assigned scope, bringing a continuous improvement mindset to every model and system you build

Minimum Requirements

Master's degree in Data Science, Computer Science, Mathematics, Statistics, or a related quantitative field
5+ years of experience as a Data Scientist working with time series and time studies data within the semiconductor, manufacturing, or facilities domain
Demonstrated experience deploying enterprise-scale Agentic AI solutions across a large organization
Deep proficiency in Python and SQL for data processing, feature engineering, and ML model development
Hands-on experience with time series methods including anomaly detection, forecasting, and signal processing (e.g., ARIMA, Prophet, LSTM, Isolation Forest, deep learning, or equivalent)
Experience with MLOps practices including model versioning, monitoring, and CI/CD for ML pipelines
Demonstrated ability to translate complex operational problems into production-grade analytical solutions
Familiarity with AI-assisted development tools as a productivity accelerator

Preferred Qualifications

Ph.D. in Data Science, Computer Science, Mathematics, Statistics, or a related quantitative field
Proven track record of leading efforts to deploy and scale enterprise-wide Agentic AI solutions in a manufacturing or industrial setting
Familiarity with semiconductor fab operations, facilities systems, equipment maintenance processes, or ESH data
Experience with CMMS (Computerized Maintenance Management Systems), Supervisory Control and Data Acquisition systems (SCADA), or semiconductor facilities equipment data
Hands-on experience with agentic frameworks, MCP, A2A, or LLM integration in production systems
Strong foundation in statistics and experimental design for validating model performance in operational environments
Excellent communication skills for presenting model insights and AI strategy to technical and non-technical stakeholders at all levels
Experience training, mentoring, leading others

TI does not make recruiting or hiring decisions based on citizenship, immigration status or national origin. However, if TI determines that information access or export control restrictions based upon applicable laws and regulations would prohibit you from working in this position without first obtaining an export license, TI expressly reserves the right not to seek such a license for you and either offer you a different position that does not require an export license or decline to move forward with your employment.

Why TI?

The future starts here. As a TIer, you'll play a critical role in defining the next era of semiconductor technology and help create the innovations that shape the world around us.
Surround yourself with a team of innovators who value your unique perspective and will challenge you to bring your best self to work every day. We believe that fostering a culture of collaboration fuels both personal growth and technological breakthroughs. Explore our company culture.
At TI, your success goes beyond your work. Take advantage of comprehensive benefits designed to support your total well-being at work and in life, from competitive compensation to extensive health coverage and wellness programs. Learn more about our benefits offerings.

About Texas Instruments

Texas Instruments Incorporated (Nasdaq: TXN) is a global semiconductor company that designs, manufactures and sells analog and embedded processing chips for markets such as industrial, automotive, data center, personal electronics and communications equipment. At our core, we have a passion to create a better world by making electronics more affordable through semiconductors. This passion is alive today as each generation of innovation builds upon the last to make our technology more reliable, more affordable and lower power, making it possible for semiconductors to go into electronics everywhere. Learn more at TI.com.

Texas Instruments is an equal opportunity employer and supports a diverse, inclusive work environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, creed, disability, genetic information, national origin, gender, gender identity and expression, age, sexual orientation, marital status, veteran status, or any other characteristic protected by federal, state, or local laws.

If you are interested in this position, please apply to this requisition.

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More about this job

Skills

Manage quantitative data
Forecasting
Manufacturing processes
ML
Data analysis
Process improvement
Computer science
Statistics
Python
SQL
Process data
Signal processing
Deep learning
CI/CD
Equipment maintenance
CMMS
Data acquisition systems
SCADA
Communication skills
Coaching
Lead others
Recruitment

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