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Data Scientist Machine Learning Jobs in West Virginia

Govcio LLC

Senior Data Scientist

Kearneysville, WV · On-site

$133K - $169K/yr

Proactively research and recommend emerging AI, machine learning, and advanced analytics ... learning models and data science solutions using Python. * Proven experience building and ...

Mazda Motor Corporation

Data Scientist

Charleston, WV · On-site

The Data Scientist is responsible for mining big data, interpreting and analyzing highly complex ... Applies advanced statistical techniques and machine learning algorithms to identify correlations ...

GDIT

Data Scientist Manager

WV · On-site +1

$129K - $155K/yr

May develop processes and machine learning based tools to monitor and analyze model performance and ... data science and engineering at GDIT and you'll find endless opportunities to grow alongside ...

Coalition, Inc.

WV

$200K/yr

About the role Coalition's machine learning models are only as good as the data they're trained on ... Work with ML engineers, data scientists, and product managers to translate model requirements into ...

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All JobsData Scientist Machine Learning JobsData Scientist Machine Learning Jobs in West Virginia

Data Scientist Machine Learning information

See West Virginia salary details

$29K

$95K

$152.1K

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

As of Jul 27, 2026, the average yearly pay for data scientist machine learning in West Virginia is $95,020.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,300.00 and $105,300.00 per year, depending on experience, location, and employer.

What is a Data Scientist Machine Learning job?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the key skills and qualifications needed to thrive in the Data Scientist Machine Learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

Is 40 too late for data science?

Data scientists can enter the field at any age, including 40 or older, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and machine learning tools. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and while AI automation tools can assist with certain tasks, MLEs are essential for creating and maintaining complex systems. AI is a tool that enhances their work but does not replace the need for skilled professionals who understand data, algorithms, and system integration.

Which 5 jobs will survive AI?

Data Scientist Machine Learning roles are likely to persist as they require complex problem-solving, domain expertise, and the ability to interpret and communicate insights from data. Jobs that involve creativity, emotional intelligence, and strategic decision-making, such as healthcare professionals, educators, and skilled trades, are also expected to remain resilient despite AI advancements.

What are the typical day-to-day responsibilities of a Data Scientist Machine Learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

Do data scientists do machine learning?

Yes, data scientists often use machine learning techniques to analyze data, build predictive models, and extract insights. Proficiency in programming languages like Python or R and understanding of algorithms are essential skills for applying machine learning in their work.
What are the most commonly searched types of Data Scientist Machine Learning jobs in West Virginia? The most popular types of Data Scientist Machine Learning jobs in West Virginia are:
What are popular job titles related to Data Scientist Machine Learning jobs in West Virginia? For Data Scientist Machine Learning jobs in West Virginia, the most frequently searched job titles are:
What job categories do people searching Data Scientist Machine Learning jobs in West Virginia look for? The top searched job categories for Data Scientist Machine Learning jobs in West Virginia are:
Data Scientist Machine Learning jobs near you
Infographic showing various Data Scientist Machine Learning job openings in West Virginia as of July 2026, with employment types broken down into 1% As Needed, 78% Full Time, 16% Part Time, 1% Temporary, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $95,020 per year, or $45.7 per hour.
Senior Data Scientist

Senior Data Scientist

Govcio LLC

Kearneysville, WV • On-site

$133K - $169K/yr

Full-time

Posted 28 days ago

GovCIO rating

7.5

Company rating: 7.5 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

112th of 230 rated it services

Job description

GovCIO is seeking a Senior Data Scientist to support a critical government computer system for the U.S. Coast Guard (USCG) Data & AI Integration Team. This role is primarily responsible for integrating AI/ML models, developing robust data pipelines, and implementing enterprise-level data management within the Data & AI Governance framework. This position will be located in Kearneysville, WV, and will be a hybrid position.
Responsibilities
As a Senior Data Scientist, you will serve as a primary technical resource and force multiplier for providing advanced analytical services and technical leadership across the Coast Guard's mission domains. You will design, build, and sustain shared data platforms to transform raw data into operational intelligence. Key responsibilities include:
  • Design, build, and integrate advanced AI/ML models and statistical algorithms into shared data platforms to enable data-driven decision dominance.
  • Develop and optimize robust data pipelines, automated ETL/ELT workflows, and analytical services to process enterprise-level data for operational use.
  • Enforce data governance standards, data management policies, and security controls across all integrated data assets and analytical models.
  • Deliver centralized, secure, and reusable data products that empower Product Teams to build interoperable, decision-support applications.
  • Provide technical leadership and architectural guidance to accelerate secure modernization, reduce technical debt, and ensure system resilience.
  • Collaborate with cross-functional teams, port authorities, and commercial partners to enable seamless data sharing, integration, and interoperability.
  • Proactively research and recommend emerging AI, machine learning, and advanced analytics technologies to support Force Design 2028 objectives.
  • Ensure all automated models and data services strictly comply with federal security standards, government baselines, and DISA STIGs.

Qualifications
High School with 9+ years (or commensurate experience)
Required Skills & Experience
  • DoD 8570 IAT Level II certification (Security+ CE, CySA+, CCNA Security).
  • Experience developing, training, and deploying enterprise-level machine learning models and data science solutions using Python.
  • Proven experience building and maintaining large-scale data pipelines, API frameworks, or cloud-based analytical environments.
  • Comprehensive operational understanding of data governance practices, data architecture principles, and secure data management.
  • Strong experience utilizing advanced database languages (such as SQL) and modern big data technologies to manipulate complex datasets.
  • Proficiency tracking, managing, and documenting analytical workflows within enterprise environments using tools like Jira or Azure DevOps.
  • Strong foundational understanding of diverse IT domains including enterprise virtualization, cloud architecture, geospatial services, and network boundaries.

Clearance Required: Active Secret Clearance
Preferred Skills & Experience
  • Experience supporting U.S. Coast Guard, Department of Homeland Security (DHS), or federal maritime mission programs.
  • Familiarity with USCG Force Design 2028 objectives or PEO C5I enterprise data environments.
  • Relevant professional certifications highly preferred (e.g., AWS Certified Data Analytics, Azure Data Scientist Associate, or Python/Data Science credentials).
  • Familiarity with geospatial data analysis (GIS) and integrating spatial modeling into enterprise decision-support applications.
  • Understanding of secure MLOps practices, containerized model deployment (Kubernetes/Docker), and automated AI/ML security gating.

#JP #USCG #DICE
Posted Salary Range
USD $133,000.00 - USD $169,000.00 /Yr.

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