Data Scientist

Texas Instruments
Dallas
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 5+ yearsEducation: mastersSkills: ["Self-directed","Communication","Ownership","Continuous improvement","Stakeholder collaboration"]

Build production-grade anomaly detection and forecasting systems for facilities operations by applying deep time series expertise. Partner with operational and engineering teams to translate complex sensor and process data into reliable analytical solutions, and deploy intelligent Agentic AI workflows at enterprise scale. Establish technical strategy, improve end-to-end ML pipelines (including MLOps and CI/CD), and mentor others through model reviews and knowledge sharing across global manufacturing and facilities environments.

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FursaFursa
Texas Instruments
Texas Instruments
2 days ago

Data Scientist

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Source: Company careers pageValidated by: Fursa AI
Last checked: 17 hours agoStatus: Live

Job Summary

Build production-grade anomaly detection and forecasting systems for facilities operations by applying deep time series expertise. Partner with operational and engineering teams to translate complex sensor and process data into reliable analytical solutions, and deploy intelligent Agentic AI workflows at enterprise scale. Establish technical strategy, improve end-to-end ML pipelines (including MLOps and CI/CD), and mentor others through model reviews and knowledge sharing across global manufacturing and facilities environments.
Location: Dallas
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Engage with operational and engineering stakeholders to map and extract value from complex time series data into production-grade models.
  • •Develop and deploy anomaly detection, predictive maintenance, and forecasting models using equipment sensor data, facility operations data, and manufacturing process signals.
  • •Design and implement end-to-end ML pipelines to reduce manual analysis effort and improve decision quality at scale.
  • •Build scalable, maintainable ML solutions using clean architecture, disciplined testing, and rigorous version control.
  • •Define technical strategy for enterprise AI deployment, lead Agentic AI initiatives from POC to scaled deployment, and mentor data scientists and engineers.

Key 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 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 for anomaly detection, forecasting, and signal processing (e.g., ARIMA, Prophet, LSTM, Isolation Forest, deep learning, or equivalent).
Experience:5+ yearsSemiconductorManufacturingFacilitiesAgentic AITime seriesMLOps
Education:Master's
Skills:Self-directedCommunicationOwnershipContinuous improvementStakeholder collaboration
Tech Stack:PythonSQLTime seriesAnomaly detectionForecastingSignal processingARIMAProphetLSTMIsolation ForestDeep learningAgentic AIModel Context Protocol (MCP)Agent-to-agent (A2A)LLM integrationMLOpsModel versioningMonitoringCI/CDVersion control

Company Brief

Texas Instruments
Designs and manufactures semiconductors and analog chips used in industrial, automotive, personal electronics, communications, and enterprise systems. It is one of the world’s largest semiconductor companies, with a broad portfolio of embedded processing and power products.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Dallas, United States
Founded: 1930
WebsiteLinkedIn