Senior Data Scientist

Job Title

Senior Data Scientist

Role Summary

The Senior Data Scientist will design, implement, and deploy machine-learning and analytical solutions across the semiconductor development lifecycle. You will work in a small, high-impact team to apply mathematical and ML techniques to problems in design automation, process optimization, device modeling, verification, manufacturing yield, test analytics, and reliability prediction.

Experience Level

Senior — requires 3+ years of professional experience in data science or machine learning roles.

Responsibilities

Deliver data-driven models and tools that improve semiconductor design, manufacturing, and test outcomes; collaborate with engineering teams to operationalize solutions.

• Develop, validate, and deploy ML and statistical models across design, process, test, and manufacturing flows.
• Apply mathematical methods (optimization, linear algebra, probability, inference) to create physics-informed models and algorithms.
• Integrate analytics with engineering workflows and production systems; ensure model reliability and maintainability.
• Collaborate with cross-functional teams (design, process technology, test, manufacturing) to translate technical problems into data solutions.
• Document methods, present results to engineering stakeholders, and drive adoption of data-science tools and best practices.
• Mentor junior team members and contribute to technical publications or patents where appropriate.

Requirements

Core skills and experience required; preferred qualifications listed separately.

• Must-have: 3+ years in data science or ML roles, with experience developing and deploying models in production or engineering environments.
• Must-have: Strong mathematical foundation (calculus, linear algebra, probability, optimization, statistical inference).
• Must-have: Advanced proficiency in Python and common libraries (Pandas, NumPy, SciPy, PyTorch, TensorFlow, scikit-learn, Matplotlib).
• Must-have: Strong communication skills and ability to present complex results to engineering teams.
• Nice-to-have: Experience with big data technologies (Spark, Hadoop), cloud platforms (AWS, Azure, GCP), and SQL/NoSQL databases.
• Nice-to-have: Familiarity with semiconductor EDA tools (Cadence, Synopsys), design-of-experiments techniques, semiconductor device physics, IC design, and manufacturing/yield analytics.
• Nice-to-have: Publication record in conferences or journals and experience mentoring junior colleagues.

Education Requirements

Bachelor's, Master's, or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, Applied Mathematics, Electrical Engineering, Physics, or a related quantitative field. For recent graduates, a cumulative GPA of 3.0/4.0 or higher is specified.

About the Company

Company: Texas Instruments

Headquarters: Dallas, Texas, USA

Texas Instruments is a global semiconductor company that designs, manufactures, and sells analog and embedded processing chips for various markets including industrial, automotive, and personal electronics. The company's innovations aim to make electronics more affordable and reliable, fostering advancements in technology through each generation of semiconductors.