Senior Data Scientist

About the Opportunity

Texas Instruments is looking for a Senior Data Scientist to join a first-of-its-kind team where advanced analytics, mathematical rigor, and machine learning meet semiconductor innovation. This is a rare opportunity to be part of a small, high-impact group that is actively shaping how data-driven decisions are made at one of the world's leading semiconductor companies.

What You Will Work On

As a Senior Data Scientist, you will develop and deploy machine learning models and analytical solutions that accelerate semiconductor development and help bring new TI products to life. You will define, design, implement, and document data science solutions across the semiconductor development flow, including design automation, process technology optimization, device modeling, design verification, manufacturing yield enhancement, test data analytics, and reliability prediction.

Beyond traditional data science, you will apply cutting-edge AI/ML techniques combined with strong mathematical foundations to solve complex challenges across the semiconductor development lifecycle—from circuit design and layout optimization to process control and parametric testing. You will leverage optimization theory, linear algebra, probability theory, and statistical inference to create robust, physics-informed models that enhance design efficiency, reduce development cycles, improve yield, and ensure product quality. You will own and drive the adoption of data science tools and methodologies across design, process development, test, and manufacturing teams, and you will have the creative freedom to develop novel ideas that can be patented and published. You will also gain deep exposure to Semiconductor Physics, IC Design, Process Technology, and Manufacturing Operations through formal learning, projects, and on-the-job experiences that will broaden your knowledge and accelerate your growth at TI.

Qualifications

Minimum Requirements:

• Bachelor’s or Master's or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, Applied Mathematics, Electrical Engineering, Physics, or a related quantitative field
• 3+ years of professional experience in data science or machine learning roles
• Cumulative 3.0/4.0 GPA or higher (for recent graduates)
• Strong foundation in mathematical concepts including calculus, linear algebra, probability theory, and optimization

Preferred Qualifications:

• Strong mathematical skills in linear algebra, multivariate calculus, optimization theory, probability, and statistical inference
• Proven experience developing and deploying ML models in production or engineering environments
• Advanced proficiency in Python and packages such as Pandas, NumPy, SciPy, PyTorch, TensorFlow, scikit-learn, and Matplotlib
• Deep knowledge of ML concepts including Neural Networks, Deep Learning, Regression, Clustering, and their mathematical foundations
• Ability to derive algorithms from first principles and apply mathematical modeling to physical systems
• Experience with big data technologies (Spark, Hadoop), cloud platforms (AWS, Azure, GCP), and SQL/NoSQL databases is a plus
• Familiarity with semiconductor EDA tools (Cadence, Synopsys) or design of experiments (DOE) techniques is a plus
• Strong communication skills with ability to present complex findings to cross-functional engineering teams
• Demonstrated problem-solving skills with strong mathematical reasoning
• Ability to work collaboratively across time zones and mentor junior team members
• Publication record in top-tier conferences or journals is a plus