Analog Circuit Design Engineer - AI/ML methodology

About the Opportunity
Are you a data scientist who thinks in algorithms, mathematical proofs, and insights? 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.
Bring your data science expertise, mathematical prowess, and passion for semiconductor technology to this role and make an impact across the company!
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

Skills
Python, AWS, Azure, GCP, SQL, Hadoop, Machine Learning, Deep Learning, Data Analysis, Pandas

Experience
3+ yrs