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Scientist Python Jobs in Kansas (NOW HIRING)

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Fluency with a deep learning framework and Python Nice to Have Experience * Contributions to ...

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Fluency with a deep learning framework and Python Nice to Have Experience * Contributions to ...

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Fluency with a deep learning framework and Python Nice to Have Experience * Contributions to ...

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Fluency with a deep learning framework and Python Nice to Have Experience * Contributions to ...

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Fluency with a deep learning framework and Python Nice to Have Experience * Contributions to ...

Showing results 21-40

Scientist Python information

How does a Scientist Python typically collaborate with other team members during research and development projects?

Scientist Python professionals frequently work in multidisciplinary teams, collaborating closely with data scientists, domain experts, and software engineers. They are often responsible for developing and implementing Python-based models or algorithms, then integrating their work with broader research goals or product pipelines. Regular communication, code reviews, and shared documentation are common practices to ensure alignment and reproducibility. This collaborative environment offers opportunities to learn from peers and contribute to diverse projects, fostering both technical and professional growth.

What does a Scientist Python do?

A Scientist Python, often referred to as a Python Scientist or Data Scientist specializing in Python, uses the Python programming language to analyze data, build predictive models, and solve scientific or business problems. They work with large datasets, apply statistical and machine learning techniques, and create visualizations to interpret results. Their work often involves writing code to clean, manipulate, and analyze data efficiently. Python's extensive libraries, such as Pandas, NumPy, and SciPy, make it a popular choice for scientific computing and data science tasks.

What are the key skills and qualifications needed to thrive as a Scientist Python?

To thrive as a Scientist Python, you need strong programming skills in Python, a solid background in scientific methods or data analysis, and typically an advanced degree in a relevant field such as computer science, physics, or biology. Experience with data analysis libraries (e.g., NumPy, pandas, SciPy), machine learning frameworks (e.g., scikit-learn, TensorFlow), and version control systems is commonly required. Critical thinking, effective communication, and problem-solving abilities help distinguish top performers in this role. These skills enable efficient data-driven research, reproducible scientific workflows, and successful collaboration in multidisciplinary environments.

How much does a scientist Python make?

A Python scientist, often called a data scientist or machine learning engineer, typically earns between $80,000 and $130,000 annually, depending on experience, location, and industry. Advanced skills in Python, data analysis, and machine learning tools can lead to higher salaries, especially in tech hubs or specialized sectors.

What is the difference between Scientist Python vs Data Analyst Python?

AspectScientist PythonData Analyst Python
Required CredentialsBachelor's or Master's in Science, Data Science, or related fields; Python proficiencyBachelor's in Statistics, Data Analysis, or related fields; Python skills
Work EnvironmentResearch labs, R&D departments, tech companiesBusiness intelligence teams, marketing, finance departments
Employer & Industry UsageResearch institutions, tech firms, healthcareCorporate, finance, retail, marketing
Common Search & ComparisonYesYes

Scientist Python and Data Analyst Python roles share similar skills like Python programming and data handling. However, Scientists typically focus on research, experimentation, and developing new models, often working in research-heavy environments. Data Analysts concentrate on interpreting existing data to inform business decisions, working mainly in corporate settings. Both roles require strong analytical skills and Python expertise, but their focus and work environments differ significantly.

Which scientist Python job is in demand?

Data scientist and machine learning engineer roles that require Python skills are currently in high demand across various industries. These positions often seek proficiency in libraries like Pandas, NumPy, and TensorFlow, along with experience in data analysis, modeling, and visualization. Strong programming skills, relevant certifications, and knowledge of cloud platforms can enhance job prospects in this field.
What are popular job titles related to Scientist Python jobs in Kansas? For Scientist Python jobs in Kansas, the most frequently searched job titles are:
What cities in Kansas are hiring for Scientist Python jobs? Cities in Kansas with the most Scientist Python job openings:
Infographic showing various Scientist Python job openings in Kansas as of August 2026, with employment types broken down into 1% Internship, 87% Full Time, 4% Part Time, and 8% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution.

Lead Applied Scientist, Marketing

Socket.dev

Columbus, KS • On-site

Other

Posted 4 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 world’s leading brands through data-driven content and technology.

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

WHY JOIN US?

At Launch Potato, you’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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