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Remote Python Data Analysis Jobs in Charlotte, NC

Analyze and annotate complex biological data sets, focusing on applications relevant to medicinal chemistry. * Provide feedback and domain-specific insights to improve AI models in computational ...

Director of Data Science

Charlotte, NC · On-site +1

$153K - $229K/yr

Qualifications: 8+ years of relevant analytical experience recommended. Master's or Ph.D. in ... Candidates who do not live near an office may be considered for a remote work arrangement with ...

Lead Analytics Consultant

Charlotte, NC · On-site +1

$110K - $179K/yr

Experience in working with Starburst or Dremio data virtualization tools * Experience in developing and supporting BI/Analytics tools Desired Qualifications: * Python, PySpark, Linux Command Line ...

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Remote Python Data Analysis information

See Charlotte, NC salary details

$12

$57

$84

How much do remote python data analysis jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for remote python data analysis in Charlotte, NC is $57.26, according to ZipRecruiter salary data. Most workers in this role earn between $47.21 and $65.05 per hour, depending on experience, location, and employer.
What are the most commonly searched types of Python Data Analysis jobs in Charlotte, NC? The most popular types of Python Data Analysis jobs in Charlotte, NC are:
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What cities near Charlotte, NC are hiring for Remote Python Data Analysis jobs? Cities near Charlotte, NC with the most Remote Python Data Analysis job openings:

SS Hackathon - AI Developer / AI Engineer

NEOGOV - Test

Concord, NC • On-site, Remote

Other

Medical, Dental, Vision, Retirement

Re-posted 22 days ago


Job description

Description Neogov is at the forefront of digital innovation, leveraging cutting-edge technology to solve complex problems and transform industries. We are seeking a talented AI Developer to join our dynamic team and help us create intelligent, scalable solutions that drive business impact. Example of Duties Develop AI Models: Design, build, train, and test machine learning (ML) and deep learning models to address specific business challenges, such as natural language processing (NLP), computer vision, or predictive analytics.

Data Handling: Collaborate with data scientists and engineers to collect, clean, preprocess, and analyze large datasets to ensure data quality and availability for model training. Integrate AI Solutions: Deploy AI models into production environments and seamlessly integrate them with existing systems, applications, and APIs. Optimize Performance: Monitor, evaluate, and fine-tune AI models and applications for performance, accuracy, and scalability.

Collaborate & Communicate: Work effectively within multidisciplinary teams, articulating complex technical concepts and findings to both technical and non-technical stakeholders. Research & Innovation: Stay updated with the latest advancements in AI technologies, tools, and industry trends to propose innovative solutions. Typical Qualifications Education:Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related quantitative field.

Experience:Proven experience as an AI Developer, Machine Learning Engineer, or similar role. Programming Proficiency:Strong coding skills in Python, Java, R, and/or C++. AI Frameworks:Hands-on experience with AI/ML frameworks and libraries such asTensorFlow,PyTorch, scikit-learn, or Keras.

Technical Knowledge:Solid understanding of machine learning algorithms, neural networks, data structures, and software architecture. Problem-Solving:Excellent analytical and problem-solving skills with attention to detail. Supplemental Information Experience with cloud computing platforms likeAWS, Google Cloud (GCP), or Azure for model deployment and scaling.

Familiarity with DevOps practices and MLOps tools (e.g., Docker, Kubernetes, MLflow). Knowledge of big data technologies such as Hadoop or Spark. Benefits Competitive salary and compensation package

Comprehensive health, dental, and vision insurance. [401(k) matching or retirement plan]. Flexible work environment/remote options.

Opportunities for continuous learning and professional development (e.g., conference sponsorships, training stipends).