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Data Scientist Jobs in Kansas (NOW HIRING)

YOUR ROLE Own the full data science engine for a priority vertical, from business problem to deployed model to live ROAS performance, driving measurable revenue and media efficiency. This is a hands ...

Project Overview We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help ...

Project Overview We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help ...

Project Overview We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help ...

Project Overview We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help ...

Project Overview We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help ...

Data Architect

Kansas City, KS ยท Hybrid

$60 - $77.25/hr

Bachelor's degree in software engineering, computer science, computer information systems, or related degree; or commensurate professional experience * 8-15 years of Data Architecture experience.

Work as a Data Scientist, Data Analyst, Devops SWE, or SRE. * Work in an office (unless you want to, but you'd be by yourself). Temporal is a fully-remote company. * Commit code that's poorly-tested ...

Showing results 21-38

Data Scientist information

See Kansas salary details

$33.4K

$109.5K

$175.2K

How much do data scientist jobs pay per year?

As of Aug 8, 2026, the average yearly pay for data scientist in Kansas is $109,464.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,800.00 and $121,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks, data visualization tools, and big data platforms like TensorFlow, Tableau, and Hadoop, as well as certifications in data science, are highly valued. Excellent problem-solving skills, curiosity, and the ability to communicate complex findings clearly set outstanding data scientists apart. These skills and qualities are crucial for extracting actionable insights from data, driving business decisions, and collaborating effectively with stakeholders.

What do data scientists do?

Data scientists collect, confirm, and interpret data to determine useful information for their employer. They help organizations identify patterns and trends in their data to provide information about lucrative opportunities, necessary improvements, and potential innovations. The information data scientists get from the records they gather helps businesses make major decisions in critical areas, such as product development, sales and marketing techniques, and client retention. Data scientists are highly educated; the majority of them have at least a master's degrees, and many have doctorates. Data scientists are valuable members of organizations in many different industries, including pharmaceuticals, manufacturing, and banking.

Is a data scientist job still in demand?

Yes, data scientist roles remain in high demand across various industries due to the increasing reliance on data-driven decision making. Skills in machine learning, statistical analysis, and programming languages like Python or R are highly valued, and employment opportunities continue to grow as organizations seek to leverage big data for competitive advantage.

Is data science a math heavy field?

Data scientists rely heavily on mathematics, including statistics, linear algebra, and calculus, to analyze data and develop models. Strong math skills are essential for tasks like machine learning, data analysis, and algorithm development, often complemented by programming in languages such as Python or R. However, practical skills in data manipulation and domain knowledge are also important for success in the field.

What is the difference between Data Scientist vs Data Analyst?

AspectData Scientist
Required CredentialsDegree in Computer Science, Statistics, or related field; often requires advanced degrees
Work EnvironmentResearch and development, predictive modeling, machine learning projects
Employer & Industry UsageTech companies, finance, healthcare, consulting firms
Common Search & ComparisonOften compared due to overlapping skills in data analysis and modeling

Data Scientists focus on building predictive models, advanced analytics, and machine learning, often requiring higher-level technical skills and education. Data Analysts primarily interpret existing data, generate reports, and support decision-making with descriptive analytics. While both roles analyze data, Data Scientists handle complex modeling and predictive tasks, whereas Data Analysts focus on data interpretation and reporting.

What are some typical projects data scientists work on, and how do they collaborate with other teams?

Data Scientists often work on projects such as building predictive models, analyzing large datasets to uncover trends, and developing data-driven solutions to business problems. They regularly collaborate with cross-functional teams, including software engineers, data engineers, and business analysts, to ensure that their insights are actionable and aligned with business goals. Effective communication and teamwork are essential, as Data Scientists frequently need to present complex findings to non-technical stakeholders and incorporate feedback from various departments.
What are the most commonly searched types of Data Scientist jobs in Kansas? The most popular types of Data Scientist jobs in Kansas are:
What are popular job titles related to Data Scientist jobs in Kansas? For Data Scientist jobs in Kansas, the most frequently searched job titles are:
What cities in Kansas are hiring for Data Scientist jobs? Cities in Kansas with the most Data Scientist job openings:
What are popular job titles related to Data Scientist jobs in KS? For Data Scientist jobs in KS, the most frequently searched job titles are:
Infographic showing various Data Scientist job openings in Kansas as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $109,464 per year, or $52.6 per hour.

Staff Data Scientist, Marketing

Socket.dev

Columbus, KS โ€ข On-site

Other

Posted 5 days ago


Job description

WHO ARE WE?

Launch Potato is a profitable digital media company that reaches over 30M+ monthly visitors through brands such as FinanceBuzz, All About Cookies, and OnlyInYourState.

As The Discovery and Conversion Company, our mission is to connect consumers with the worldโ€™s leading brands through data-driven content and technology.

Headquartered in South Florida with a remote-first team spanning over 15 countries, weโ€™ve built a high-growth, high-performance culture where speed, ownership, and measurable impact drive success.

WHY JOIN US?

At Launch Potato, youโ€™ll accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers.

MUST HAVE:
  • Proven experience in digital marketing, performance marketing, or the leadgen industry
  • Building adtech algorithms and supporting user acquisition or paid media modeling (highly desired)
  • Strong modeling fundamentals: the ability to build effective models that drive business impact
  • Multi-year, hands-on experience building and deploying ML solutions in the AWS cloud
  • Hands-on experience across core technique areas: multi-armed bandit / reinforcement learning, recommendation and ranking systems (content-based, collaborative filtering, hybrid), funnel and monetization optimization, LTV modeling
  • Expert Python and SQL
EXPERIENCE:

5+ years in a hands-on, in-the-weeds applied data science role delivering measurable business impact.

YOUR ROLE

Own the full data science engine for a priority vertical, from business problem to deployed model to live ROAS performance, driving measurable revenue and media efficiency. This is a hands-on, in-the-weeds role: you are heavily immersed in the data and the modeling, framing the business problem directly with stakeholders, building and validating the model, handing the ML-engineering last mile to your ML engineering partner, and staying engaged through deployment, monitoring, and performance analysis.

You will start focusing on Insurance and Advertiser Quality, with scope that broadens over time. Your primary metric is ROAS.

OUTCOMES
  • Own the Insurance vertical's primary modeling work end-to-end with measurable ROAS impact
  • Deliver buying models that maintain positive ROAS and quality
  • Drive lead quality improvements across our portfolio of brands: Messaging, Funnels, Content/Listicles, and more resulting in measurable impact to revenue growth
  • Establish trusted, direct partnership with vertical business stakeholders
  • Produce trusted output: validated, documented, low correction burden
  • Identify and leverage net-new modeling opportunities the business has not flagged
COMPETENCIES
  • Business-first framing: Starts with the problem and the metric, not the model.
  • Full-stack ownership: Stays engaged from problem definition through deployed performance
  • Proactive communication: Closes loops without being chased
  • Collaborative: Leans on ML engineering for the last mile rather than working solo
  • Coachable: Seeks feedback and turns it into visible behavior change
  • Curiosity paired with delivery discipline
NICE TO HAVES
  • Sophisticated ML at companies where paid digital media is core to the business model
  • Creative embeddings work: incorporating embeddings of creatives, videos, headlines, and search into paid media models
  • Insurance domain experience
  • Creating state-of-the-art Ad Ranking algorithms
  • Modeling against ad-platform data points (Google, Meta, native)
  • LLMs / deep learning applied to personalization or content
  • Familiarity with Looker

Since day one, we've been committed to having a diverse, inclusive team and culture. We are proud to be an Equal Employment Opportunity company. We value diversity, equity, and inclusion.

We do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

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