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Data Science Phd Jobs in Kansas (NOW HIRING)

Knowmadics

Data Scientist

Wichita, KS · On-site

Graduate-level education (Master'sor PhD) in a quantitative field such as natural sciences ... Exposure to big data environment including tools for large-scale data storage and sensor-based data ...

Nuvative Inc

Data Scientist

Wichita, KS · On-site

QUALIFICATIONS * BS, MS or PhD in Data Science, Analytics, Statistics, Applied Mathematics, or a related field (with a minimum of 3 years of experience preferred). * In depth knowledge and ...

Nuvative Inc

Data Scientist

Wichita, KS · On-site

QUALIFICATIONS * BS, MS or PhD in Data Science, Analytics, Statistics, Applied Mathematics, or a related field (with a minimum of 3 years of experience preferred). * In depth knowledge and ...

StackAdapt

... on data-driven insights. What you'll bring to the table: * 3+ years of industry experience * Have a Masters degree or PhD in Computer Science, Statistics, Operations Research, or a related field ...

CrowdStrike

Master's degree or PhD in Computer Science, Data Engineering, or a related STEM field, or equivalent practical experience. * 10+ years of progressive experience in Data Engineering/Platform ...

CareDx

Medical Science Liaison - Central

Topeka, KS · On-site +1

$155K - $170K/yr

PharmD, PhD, or MD. * Prior experience in an MSL role highly preferred and/or introduction of new ... data, interpret clinical scenarios, and communicate diagnostic and management issues in transplant ...

Benedictine College

Biomedical Science Faculty

Atchison, KS · On-site

$23.50 - $31.25/hr

... mapping, and data analysis. 7. Provide lectures in discipline of specialty and facilitate ... Terminal degree (DO, MD, PhD, EdD) 2. Minimum of 5 years full time, uninterrupted experience in ...

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Data Science Phd information

What can you do with a doctorate in data science?

A doctorate in data science prepares individuals for advanced roles such as data scientist, research scientist, or machine learning engineer, often involving complex data analysis, modeling, and algorithm development. It enables expertise in programming languages like Python or R, statistical methods, and data management tools, opening opportunities in academia, industry, and research institutions.

What are the key skills and qualifications needed to thrive as a Data Science PhD, and why are they important?

To thrive as a Data Science PhD, you need advanced expertise in statistics, machine learning, data analysis, and a doctoral degree in a quantitative field. Proficiency in programming languages like Python or R, experience with big data frameworks (e.g., Spark, Hadoop), and familiarity with data visualization tools are typically required. Critical thinking, problem-solving, and strong communication skills help you translate complex data insights for diverse stakeholders. These skills are vital for driving innovative research, making data-driven decisions, and contributing impactful solutions in data-centric environments.

Is PhD worth it for data science?

A PhD in data science can enhance expertise in advanced analytics, research, and specialized skills, which may lead to higher-level roles and increased salary potential. However, it also requires significant time and financial investment, and many data science positions value practical experience and skills in programming, machine learning, and data manipulation over formal degrees.

What is the salary of a PhD in data scientist?

A Data Science PhD typically earns between $100,000 and $150,000 annually, depending on experience, industry, and location. Advanced degrees and expertise in machine learning, statistical analysis, and programming tools like Python or R can lead to higher compensation, especially in tech and research sectors.

What are some common challenges faced by Data Science PhDs when transitioning from academia to industry roles?

Data Science PhDs often encounter challenges such as adapting to the faster pace and collaborative nature of industry projects compared to academic research. In industry, there is a greater emphasis on delivering practical solutions within tight deadlines and working closely with cross-functional teams like engineering and product management. Additionally, data science work in industry may require balancing technical rigor with business impact, often prioritizing actionable insights over exhaustive analysis. Building strong communication and stakeholder management skills can help ease this transition.

Is 40 too late for data science?

Data science PhDs can pursue careers at any age, including at 40 or older. Success depends on skills, experience, and continuous learning in areas like programming, statistics, and machine learning, rather than age alone.

What is a Data Science PhD?

A Data Science PhD is a doctoral-level degree focused on advanced research in data science, which combines elements of statistics, computer science, and domain expertise. Students in a Data Science PhD program typically work on developing new methods for analyzing large datasets, creating machine learning algorithms, and addressing complex problems in areas such as artificial intelligence, data mining, and predictive analytics. Graduates are prepared for careers in academia, research, and industry, where they can lead data-driven projects and contribute to advancements in the field.
What are popular job titles related to Data Science Phd jobs in Kansas? For Data Science Phd jobs in Kansas, the most frequently searched job titles are:
What job categories do people searching Data Science Phd jobs in Kansas look for? The top searched job categories for Data Science Phd jobs in Kansas are:
What cities in Kansas are hiring for Data Science Phd jobs? Cities in Kansas with the most Data Science Phd job openings:
Data Science Phd jobs near you
Data Scientist

Data Scientist

Knowmadics

Wichita, KS • On-site

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Candidate should live within driving distance of the following areas: Wichita, KS;Lawton OK; or Round Rock, TX


Job Purpose/Summary

Work with our team of engineers, scientists and human factors professionals to develop machine learning and other algorithm data capabilities for cybersecurity, space, and telecommunications. This individual contributor role will involve hands-on work collecting data, developing solutions to real-world problems using machine learning. Developed solutions are actively being productionized to support ongoing cybersecurity initiatives and other crucial infrastructure and security needs.

Duties and Responsibilities

  • Collaboratively develop data collection processes designing experiments to ensure quality and usefulness of data
  • Develop and evaluate machine learning solutions to interdisciplinary problems in cybersecurity and telecommunications, working with structured (time-series, tabular) and unstructured (text, 3D) data
  • Work with human factors specialists, and data/full stack engineers to define system requirements, review developed code, and support translating statistical concepts to coworkers
  • Support documentation of analysis results for semi-technical stakeholders
  • Occasionally support technical interactions like collaboration, including defining technical requirements for external data collections, and reviewing technical work

Qualifications

  • Minimum
    • Graduate-level education (Master'sor PhD) in a quantitative field such as natural sciences, mathematics, statistics, economics, psychology, or a related discipline is preferred. Exceptional candidates with a bachelor's degree and substantial applied machine learning or data science experience may also be considered.
    • 2+ years professional experience with an open-source data science stack (e.g., pandas, numpy, pytorch, keras, tensorflow, pymc3, etc.)
    • 2+ years professional experience working with real-world, complex datasets
    • Experience communicating technical results to semi-technical audience
  • Preferred
    • Exposure to product-driven machine learning organization with deployed customer facing capabilities
    • Exposure to big data environment including tools for large-scale data storage and sensor-based data collection workflows
    • Experience with RF/Telecommunications physics, cybersecurity, or space operations
    • Experience with UAS operations, with Part 107 Remote Pilot Certification preferred

Working conditions

  • Employees may be called upon to participate in in-person meetings, trainings, or company functions at Knowmadics offices or other designated locations. Travel in support of business operations may also be required, and employees are expected to comply with these obligations as part of their position.
  • Some weekend work may be required based on project deadlines or operational needs.
  • Estimated Travel: 30-40%

Physical requirements

May include sitting or standing for extended periods, working with computers and technical equipment, and occasionally lifting or moving materials or tools.

Direct reports

None

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