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Phd In Statistics Jobs in Minnesota (NOW HIRING)

MS or PhD in Analytical Chemistry, Chemistry, Chemical Engineering, Materials Science, or a related ... Familiarity with statistical analysis tools used in analytical chemistry. * Understanding of ...

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Phd In Statistics information

What is the difference between Phd In Statistics vs Data Scientist?

AspectPhd In StatisticsData Scientist
Required CredentialsTypically a PhD in Statistics or related fieldOften a bachelor's or master's degree in a quantitative field; some roles prefer a PhD
Work EnvironmentAcademic, research institutions, or specialized analytics teamsCorporate, tech companies, or consulting firms
Industry UsageResearch, academia, government, and industry R&DBusiness analytics, product development, and data-driven decision making
Common Search & ComparisonYesYes

While a Phd In Statistics focuses on advanced research, theoretical development, and academic roles, Data Scientists apply statistical and machine learning techniques to solve practical business problems. Both roles require strong analytical skills, but Data Scientists often work in more applied, industry-focused environments, whereas PhD holders may pursue research or academic careers.

What is the highest paying job with a statistics degree?

The highest paying jobs with a statistics degree often include roles such as data scientist, quantitative analyst, or actuarial scientist, with salaries exceeding $100,000 annually. Senior positions in finance, technology, or consulting firms tend to offer the highest compensation, especially for those with advanced skills in machine learning, programming, and statistical modeling.

How much can you make with a PhD in statistics?

A PhD in statistics can lead to high-paying roles such as data scientist, quantitative analyst, or research scientist, with salaries typically ranging from $90,000 to over $150,000 annually depending on experience, industry, and location. Advanced skills in programming, statistical software, and data analysis increase earning potential in this field.

Is getting a PhD in statistics worth it?

A PhD in statistics prepares individuals for advanced research, academia, and data science roles that require deep analytical skills and expertise in statistical methods. It can lead to higher-level positions and increased earning potential but involves significant time and financial investment. The decision depends on career goals and the demand for specialized statistical knowledge in the desired industry.

What can I do with PhD in statistics?

A PhD in statistics qualifies individuals for advanced roles such as data scientist, quantitative analyst, biostatistician, or research scientist. These positions often involve data analysis, modeling, and interpretation using statistical software like R or SAS, and may require collaboration across industries such as healthcare, finance, or technology.
What are popular job titles related to Phd In Statistics jobs in Minnesota? For Phd In Statistics jobs in Minnesota, the most frequently searched job titles are:
Infographic showing various Phd In Statistics job openings in Minnesota as of June 2026, with employment types broken down into 100% Full Time. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Test and Characterization Staff Engineer

skywater

Minneapolis, MN

Other

Posted 2 days ago


Job description

SkyWater is hiring a talented and motivated Test and Characterization Staff Engineer with expertise in CMOS technology. As a Test and Characterization Engineer, you will play a vital role in ensuring the functionality and performance of our advanced semiconductor devices. Your expertise will contribute to the validation, testing, and characterization of CMOS integrated circuits, leading to the development of high-quality and reliable products.

Responsibilities:

  • Test Development: Collaborate with the design and product engineering teams to develop test methodologies and test plans for CMOS devices, SRAM, and analog/digital products. Design and implement automated test programs and hardware setups using industry-standard test equipment.
  • Characterization: Conduct electrical characterization of CMOS integrated circuits to analyze their performance, including speed, power, and noise characteristics. Perform DC and AC parametric measurements to verify device and IC specifications and optimize performance.
  • Test Execution: Execute tests on CMOS devices according to established test plans. Troubleshoot and resolve issues that arise during testing, ensuring accurate and reliable measurement data.
  • Data Analysis: Analyze test data and measurement results using statistical analysis software (e.g., JMP, Minitab, Python) to extract meaningful insights and identify trends. Use this data to evaluate device performance and provide feedback to design teams for continuous improvement.
  • Yield Analysis: Collaborate with yield engineering teams to analyze test data and identify potential yield-limiting factors in the CMOS manufacturing process. Contribute to yield enhancement efforts through data-driven problem-solving.
  • Test Automation: Continuously improve test methodologies and automation scripts to enhance efficiency and reduce testing time. Implement best practices for test automation and data management.
  • Documentation: Prepare clear and comprehensive test reports, documenting test procedures, results, and observations. Present findings to cross-functional teams and management as required.
  • Collaboration: Work closely with product engineers, process engineers, and design teams to provide valuable input during the development cycle and support product validation efforts.
  • Equipment Maintenance: Ensure proper maintenance and calibration of test equipment to guarantee accurate and consistent test results.

Required Qualifications:

  • 5+ years experience with BS, 3+ years of experience with MS, 0-2 years of experience with PhD in Electrical Engineering, Electronics Engineering, or a related field with a focus on CMOS technology.
  • Demonstrated experience in CMOS test and characterization in a semiconductor manufacturing environment. Experience in sub 130nm memories technology development is a plus.
  • Test Equipment: Proficiency in using semiconductor test equipment, such as Automatic Test Equipment (ATE), oscilloscopes, function generators, Keysight test electronics, GPIB communication protocols.
  • Test software development: proficiency in one or more of the following programing languages: C, C++, C#, Java, Python, Ruby, Visual Basic.
  • Data Analysis: Strong data analysis skills using statistical analysis software and scripting languages like Python (Pandas) or MATLAB.
  • CMOS Technology: Solid understanding of CMOS device operation, and characterization techniques.
  • Test Methodologies: Familiarity with test methodologies like DC/AC parametric testing, functional testing.
  • Problem-Solving Skills: Ability to troubleshoot test and measurement issues and collaborate with different teams to find solutions.
  • Communication: Excellent verbal and written communication skills to convey technical information and collaborate effectively with cross-functional teams.
  • Attention to Detail: Strong attention to detail to ensure accurate data collection and analysis.
  • Team Player: Ability to work collaboratively in a fast-paced and dynamic environment, contributing to a positive team culture.
  • US Citizenship Required: This position will require the holding of, or ability to obtain, a US government security clearance.