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Remote Data Scientist Machine Learning Jobs in Marion, IA

Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and ... Continuous Learning: * A commitment to ongoing learning and professional development in growth ...

Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and ... Continuous Learning: * A commitment to ongoing learning and professional development in growth ...

Remote Work-at-Home MCI is one of the fastest-growing tech-enabled business services companies in ... learning and development opportunities and contribute to the success of a globally expanding ...

This role involves maintaining data integrity, evaluating partnership lifecycles, and assisting ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

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Remote Data Scientist Machine Learning information

See Marion, IA salary details

$37.4K

$122.4K

$195.9K

How much do remote data scientist machine learning jobs pay per year?

As of Sep 8, 2026, the average yearly pay for remote data scientist machine learning in Marion, IA is $122,371.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,200.00 and $135,600.00 per year, depending on experience, location, and employer.

What does a remote data scientist specializing in machine learning do?

A Remote Data Scientist specializing in Machine Learning uses advanced statistical techniques and programming skills to analyze large datasets and build predictive models, all while working from a remote location. They design, develop, and deploy machine learning algorithms to solve business problems, such as forecasting trends or automating processes. Their work often involves data cleaning, feature engineering, model selection, and collaborating with cross-functional teams to integrate these models into products or services. Remote data scientists typically use tools like Python, R, and cloud-based platforms to perform their tasks efficiently.

How do remote data scientists specializing in machine learning typically collaborate with cross-functional teams?

Remote data scientists in machine learning often work closely with product managers, engineers, and business analysts through virtual meetings, collaborative platforms, and shared documentation tools. They regularly participate in sprint planning, code reviews, and brainstorming sessions to ensure alignment with project goals. Effective communication and proactive updates are essential for overcoming the challenges of remote collaboration and maintaining project momentum. Building strong relationships with team members across different time zones helps foster innovation and ensures that machine learning solutions are well-integrated into broader business objectives.

What are the key skills and qualifications needed to thrive as a remote data scientist specializing in machine learning?

To excel as a Remote Data Scientist in Machine Learning, you need a solid background in statistics, programming (typically Python or R), and a degree in computer science, mathematics, or a related field. Familiarity with tools and frameworks such as TensorFlow, scikit-learn, PyTorch, and experience with cloud platforms like AWS or Azure are often required, along with relevant certifications. Strong problem-solving skills, effective communication, and the ability to work independently are crucial soft skills for remote collaboration and translating insights for diverse stakeholders. These competencies ensure the development of robust models, clear communication of findings, and successful project delivery in a distributed work environment.

What is the difference between Remote Data Scientist Machine Learning vs Remote Data Scientist?

AspectRemote Data Scientist Machine LearningRemote Data Scientist
Required CredentialsMaster's or PhD in Data Science, Computer Science, or related field; experience with ML frameworksSimilar educational background; may focus more on statistical analysis and data visualization
Work EnvironmentPrimarily involves developing ML models, coding in Python/R, and deploying algorithmsFocuses on data analysis, reporting, and insights generation, often with less emphasis on ML deployment
Employer & Industry UsageUsed in tech, finance, healthcare for predictive modeling and automationCommon across various industries for data analysis and business intelligence

While both roles require strong analytical skills and similar educational backgrounds, Remote Data Scientist Machine Learning specializes in developing and deploying machine learning models, whereas Remote Data Scientist focuses more on data analysis and reporting. The ML role often involves coding and algorithm development, making it more technical in nature.

What are popular job titles related to Remote Data Scientist Machine Learning jobs in Marion, IA?

For Remote Data Scientist Machine Learning jobs in Marion, IA, the most frequently searched job titles are:

Growth Hacker - Remote

EnthuZiastic

Iowa City, IA โ€ข Remote

Full-time

Re-posted 18 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

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This is a remote position.

User Acquisition:

  • Develop and execute strategies to acquire new users, customers, or leads through various channels, such as SEO, social media, content marketing, email marketing, and paid advertising.

Conversion Rate Optimization:

  • Identify areas of the user journey with conversion bottlenecks and devise experiments to optimize conversion rates, including A/B testing and landing page optimization.

Product Development:

  • Collaborate with product teams to improve user experience, optimize product features, and iterate based on user feedback to drive growth.

Customer Retention:

  • Develop strategies to increase customer retention and reduce churn through engagement, loyalty programs, and targeted communication.

Data Analysis:

  • Collect and analyze data to gain insights into user behaviour, product usage, and marketing performance.

  • Use data-driven decisions to guide growth strategies and experiments.

Viral Marketing:

  • Create and implement strategies to encourage users to refer others to the product or service through viral marketing techniques.

Content Marketing:

  • Develop and distribute high-quality content that educates, informs, and engages the target audience, driving traffic and brand awareness.

Experimentation:

  • Plan and execute rapid, iterative experiments to test growth hypotheses and identify effective strategies.

  • Continuously refine and scale strategies based on experiment results.

Marketing Automation:

  • Implement marketing automation tools and workflows to streamline and personalize user communication and engagement.

Budget Management:

  • Manage and allocate budgets effectively across various growth channels, ensuring a positive return on investment.

Reporting and Analysis:

  • Provide regular reports on growth performance, including key metrics and insights to relevant stakeholders.
Requirements

Digital Marketing Expertise:

  • Proven experience in digital marketing, with a deep understanding of various marketing channels and tools.

Analytical Skills:

  • Strong analytical and data interpretation skills, including proficiency in data analysis tools and platforms.

Technical Proficiency:

  • Familiarity with marketing automation tools, A/B testing platforms, web analytics, and data visualization tools.

Creativity:

  • Ability to think creatively and develop unique strategies to achieve growth.

Communication Skills:

  • Effective communication skills for collaborating with cross-functional teams and presenting findings and strategies to stakeholders.

Entrepreneurial Mindset:

  • A proactive and entrepreneurial spirit with a willingness to take calculated risks and adapt to changes.

Adaptability:

  • Ability to stay updated with the latest trends in marketing and technology and adapt strategies accordingly.

Project Management:

  • Strong project management skills to handle multiple growth initiatives simultaneously.

Experience with Startups:

  • Experience working in a startup environment or high-growth company is often preferred.

Continuous Learning:

  • A commitment to ongoing learning and professional development in growth hacking.
Benefits
  • Opportunity to be a part of a dynamic growth focused tech startup.

  • Great learning opportunities to develop new skills and understanding of cutting edge software tools and processes.

  • Opportunity to work closely with serial tech entrepreneurs from Silicon Valley.

  • Fun-loving environment and caring team mates and inclusive culture of the company.