Bengaluru, Karnataka, India
Open 5 months, first seen by us 168 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Develop and deploy ML models across the semiconductor development flow
Apply AI/ML and math-based methods to improve yield and product quality
Define, design, implement and document data science solutions
Drive adoption of data science tools across design, process, test and manufacturing teams
develop and deploy machine learning models and analytical solutions that accelerate semiconductor development
improve yield, and ensure product quality
define, design, implement, and document data science solutions across the semiconductor development flow
You will own and drive the adoption of data science tools and methodologies across design, process development, test, and manufacturing teams
3+ years of professional experience in data science or machine learning roles
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
Strong foundation in mathematical concepts including calculus, linear algebra, probability theory, and optimization
Advanced proficiency in Python and packages such as Pandas, NumPy, SciPy, PyTorch, TensorFlow, scikit-learn, and Matplotlib
Proven experience developing and deploying ML models in production or engineering environments
Ability to work collaboratively across time zones and mentor junior team members
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
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
Are you a data scientist who thinks in algorithms, mathematical proofs, and insights?
In the employer’s words · Read in context
Open 5 monthsWe first saw this posting 168 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 168
Up longer than most. Similar jobs usually come down between day 7 and day 56.
Well past Texas Instruments’s usual: its jobs come down by about day 12.
From 10,207 similar postings that came down, and 13 of Texas Instruments’s. Coming down is not always a hire.
7 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- 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
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Already applied? Track this application
Yes. We’ve followed one other Analog Circuit Design Engineer - AI/ML methodology job there since May 2026. It is still up.
New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
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:
Preferred Qualifications:
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Bengaluru, Karnataka, India
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