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Weekend Remote Data Scientist Jobs in Springfield, MO

Apex Systems

Principal AI Engineer

Springfield, MO · Remote

$70 - $100/hr

Remote (CST) Employment Type: Contract to Perm Rate: $70-$100 Per Hour W2 Role Overview Join our ... Bachelor's Degree or equivalent experience in Computer Science, Data Engineering, Data Science ...

Next Level Solutions

Senior Quality Engineer

Springfield, MO · On-site +1

$75.50K - $102.30K/yr

... data, identify risks, and communicate critical quality concerns to leadership • Support ... in Computer Science, Information Technology, or related field; or equivalent professional ...

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All JobsWeekend Remote Data Scientist JobsWeekend Remote Data Scientist Jobs in Springfield, MO

Weekend Remote Data Scientist information

See Springfield, MO salary details

$34.1K

$111.6K

$178.7K

How much do weekend remote data scientist jobs pay per year?

As of May 29, 2026, the average yearly pay for weekend remote data scientist in Springfield, MO is $111,646.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,600.00 and $123,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Weekend Remote Data Scientist, and why are they important?

To thrive as a Weekend Remote Data Scientist, you need strong analytical skills, expertise in statistics, and a background in computer science or mathematics, often supported by a relevant degree. Familiarity with programming languages such as Python or R, experience with machine learning libraries, and knowledge of data visualization tools and cloud platforms are typically expected. Excellent time management, self-motivation, and clear communication skills are essential for independent remote work and effective collaboration with distributed teams. These skills ensure accurate data-driven insights, efficient project delivery, and seamless coordination in a remote and flexible work environment.

What are some common challenges faced by weekend remote data scientists, and how can they be addressed?

Weekend remote data scientists often face challenges such as managing communication with teammates who work standard weekday hours and accessing time-sensitive data or support outside regular business times. To overcome these hurdles, it's important to set clear expectations with your team, utilize asynchronous communication tools (like Slack or email), and plan your tasks in advance to ensure you have all necessary resources before the weekend. Proactively updating your team on progress and any blockers can also help maintain collaboration and project momentum.

What are Weekend Remote Data Scientists?

Weekend Remote Data Scientists are professionals who work part-time or on a flexible schedule, typically during weekends, to analyze data, build models, and generate insights for organizations. They perform their duties remotely, using data science tools and techniques to solve business problems without needing to be physically present at an office. This role is ideal for those seeking work-life balance, additional income, or flexibility in their work schedule. Weekend Remote Data Scientists often collaborate with teams via virtual communication platforms and use cloud-based tools to access and analyze data securely.

What is the 80 20 rule in data science?

The 80/20 rule in data science, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or data. Data scientists often use this concept to focus on the most impactful features, data subsets, or tasks to improve model performance efficiently.

What is the difference between Weekend Remote Data Scientist vs Part-Time Data Analyst?

AspectWeekend Remote Data ScientistPart-Time Data Analyst
CredentialsBachelor's or Master's in Data Science, Statistics, or related fieldBachelor's degree in related field, often with similar certifications
Work EnvironmentRemote, flexible hours, project-basedRemote or on-site, flexible hours, project or hourly-based
Industry UsageTech, finance, healthcare, e-commerceBusiness, marketing, research, finance
Search & Comparison IntentFocus on data science skills, modeling, machine learningFocus on data analysis, reporting, visualization

The Weekend Remote Data Scientist typically works on complex data modeling and machine learning projects during weekends, requiring advanced data science skills. In contrast, a Part-Time Data Analyst focuses on data reporting, visualization, and basic analysis, often during flexible hours. Both roles are remote and part-time but differ in technical complexity and daily responsibilities.

What are popular job titles related to Weekend Remote Data Scientist jobs in Springfield, MO? For Weekend Remote Data Scientist jobs in Springfield, MO, the most frequently searched job titles are:
What job categories do people searching Weekend Remote Data Scientist jobs in Springfield, MO look for? The top searched job categories for Weekend Remote Data Scientist jobs in Springfield, MO are:
What cities near Springfield, MO are hiring for Weekend Remote Data Scientist jobs? Cities near Springfield, MO with the most Weekend Remote Data Scientist job openings:
Weekend Remote Data Scientist jobs near you
Generative AI Automation Engineer - Remote Job

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Springfield, MO • Remote

Other

Posted 6 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply