The successful candidate will hold a Bachelor's degree in Computer Science, Programming, other ... data modeling. The incumbent will have demonstrated experience developing cross capability ...
The successful candidate will hold a Bachelor's degree in Computer Science, Programming, other ... data modeling. The incumbent will have demonstrated experience developing cross capability ...
Freelance Data Science information
See Oklahoma salary details
$34.6K - $48K
2% of jobs
$48K - $61.3K
3% of jobs
$61.3K - $74.7K
6% of jobs
$74.7K - $88K
9% of jobs
$92.3K is the 25th percentile. Wages below this are outliers.
$88K - $101.4K
15% of jobs
The median wage is $110.3K / yr.
$101.4K - $114.7K
22% of jobs
$122K is the 75th percentile. Wages above this are outliers.
$114.7K - $128K
32% of jobs
$128K - $141.4K
3% of jobs
$141.4K - $154.7K
4% of jobs
$154.7K - $168.1K
1% of jobs
$168.1K - $181.4K
2% of jobs
$34.6K
$113.3K
$181.4K
How much do freelance data science jobs pay per year?
As of Sep 1, 2026, the average yearly pay for freelance data science in Oklahoma is $113,329.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,900.00 and $125,600.00 per year, depending on experience, location, and employer.
What is a freelance data scientist?
Freelance data scientists are independent professionals who analyze, interpret, and extract insights from data for clients on a project or contract basis, rather than working as full-time employees for a single organization. They leverage skills in statistics, programming, and machine learning to solve business problems, build predictive models, and visualize data. Freelance data scientists often work with multiple clients across various industries, providing flexibility and the ability to specialize in different types of data projects. Their work may include tasks such as data cleaning, exploratory data analysis, algorithm development, and reporting findings to stakeholders.
What are the key skills and qualifications needed to thrive as a freelance data scientist?
To thrive as a Freelance Data Scientist, you need strong proficiency in statistics, programming (commonly Python or R), and data analysis, often backed by a degree in a quantitative field or relevant certifications. Mastery of tools like Jupyter Notebook, SQL, machine learning libraries (e.g., scikit-learn, TensorFlow), and experience with cloud platforms are typically required. Excellent communication, self-motivation, and time management skills set successful freelancers apart by enabling effective client collaboration and project delivery. These abilities ensure you can independently deliver actionable insights and solutions that meet diverse client needs in a competitive market.
What are the most common challenges faced by freelance data scientists when working with clients remotely?
Freelance data scientists often encounter challenges such as unclear project scopes, varying data quality, and communication gaps when collaborating remotely with clients. It's essential to establish clear expectations, maintain regular updates, and set milestones to ensure both parties are aligned throughout the project. Additionally, freelancers may need to adapt to different tools or platforms based on each client's preferences, requiring flexibility and strong self-management skills. Building trust and delivering insights in a clear, actionable manner can help foster long-term client relationships.
What is the difference between Freelance Data Science vs Data Analyst?
| Aspect | Freelance Data Science | Data Analyst |
|---|---|---|
| Credentials | Typically requires a degree in data science, statistics, or related fields; certifications like CAP or Microsoft Data Analyst | Often requires a degree in statistics, mathematics, or related fields; certifications like Microsoft Data Analyst or Tableau |
| Work Environment | Independent, project-based, remote or on-site | Usually employed within organizations, working in teams or departments |
| Employer & Industry Usage | Freelance data science projects across various industries like tech, finance, healthcare | In-house roles in industries such as finance, marketing, healthcare, and retail |
Freelance Data Science involves independent, project-based work requiring advanced skills in machine learning, programming, and statistical analysis. Data Analysts typically focus on interpreting existing data, creating reports, and visualizations within organizations. While both roles require strong analytical skills, freelance data scientists often handle more complex modeling tasks, whereas data analysts focus on data interpretation and reporting.
What are the most commonly searched types of Data Science jobs in Oklahoma?
The most popular types of Data Science jobs in Oklahoma are:
What are popular job titles related to Freelance Data Science jobs in Oklahoma?
For Freelance Data Science jobs in Oklahoma, the most frequently searched job titles are:
What job categories do people searching Freelance Data Science jobs in Oklahoma look for?
The top searched job categories for Freelance Data Science jobs in Oklahoma are:
Full-time
Re-posted 21 days ago
Job description
Technical Lead, ERP and Centralization Project
Apply now Job no: 492638
Work type: Consultant - Columbia University
Location: USA (non-CU jobs)
Categories: Technical/Clinical/Quality Improvement/Training
ICAP at Columbia University, a global health leader situated within the Columbia University Mailman School of Public Health in New York City, seeks highly qualified candidate to serve as Technical Lead, ERP and Centralization Project to be based in New York. The incumbent will lead all Technology based initiatives for the development and implementation of a new ERP solution and its dependencies for ICAP.
The successful candidate will hold a Bachelor's degree in Computer Science, Programming, other related discipline or the equivalent work and progressive technology management experience and a minimum of seven (7) years technical leadership experience in the area of enterprise software and new product development; experience with SDLC, agile development methods, and common app development tools; extensive technical project management experience with a history of bring projects in on-time and on-budget; ability to interact at all the levels of an organization - presenting ideas, promoting best practices and coaching staff as needed; and a background in programming and data modeling.
The incumbent will have demonstrated experience developing cross capability solutions with integrations across multiple systems, both new and legacy and experience managing diverse, distributed technical teams - direct reports and dotted lines; freelancers, permanent, and partner and vendor-managed staff, based domestically and abroad.
To view a full job description, please click here - ERP Technical Lead Propsed.pdf.
The position is contingent upon availability of grant funding.
Columbia University is an equal opportunity and affirmative action employer. It does not discriminate against employees or applicants for employment on the basis of race, color, sex, gender, religion, creed, national and ethnic origin, age, citizenship, status as a perceived or actual victim of domestic violence, disability, marital status, sexual orientation, status as a Vietnam era or disabled veteran, or any other legally protected status.
Advertised: 31 Jan 2020 Eastern Standard Time
Applications close:
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