1

Data Science Jobs in West Virginia (NOW HIRING)

Bachelor's degree it IT, Computer Science, Data Science, Industrial Engineering, IS/IT, or related field required * 5+ years of data analysis experience required, preferably in manufacturing * Strong ...

WV · On-site

$200K/yr

Work with ML engineers, data scientists, and product managers to translate model requirements into well-structured labeling tasks. Challenge teams on task design when labeling instructions are ...

Data Science and Data Engineering Job Qualifications: Skills: Data Analytics, Python for Data Analysis, Statistical Analysis Certifications: None Experience: 4 + years of related experience US ...

Bachelor's degree it IT, Computer Science, Data Science, Industrial Engineering, IS/IT, or related field required * 5+ years of data analysis experience required, preferably in manufacturing * Strong ...

Bachelor's degree in engineering, data science, information management, computer science, or a related technical field. * At least 3-5 years of experience in technical data management, database ...

$26.66 - $28.48/hr

Bachelor's degree with major in Data Science, Psychology, Statistics, Computer Science or related field, and 0 to 1 year of experience, or an equivalent combination of education and experience ...

Data Engineer, Security

WV · On-site +1

$163K/yr

You will be the go-to partner for Stakeholders, Research team and Data Science team requiring Cyber Security related Data. As a Data Engineer, you will design and develop our data lifecycle ...

Bachelor's degree in Accounting, Finance, Information Systems, Computer Science, Statistics, Data Science, Engineering, or a related quantitative field. * CPA or other relevant professional ...

Data Science and Data Engineering Job Qualifications: Skills: Data Analytics, Data Warehousing (DW), Enterprise Data, Relational Data Modeling Certifications: None Experience: 10 + years of related ...

Data Governance Lead

WV · On-site +1

Data Science and Data Engineering Job Qualifications: Skills: Change Management, Data Quality, Governance Framework, Governance Structures, Process Governance Certifications: None Experience: 10 + ...

Senior Data Architect

WV · On-site +1

$195K - $264K/yr

Data Science and Data Engineering Job Qualifications: Skills: Data Engineering, Data Lake, Data Warehousing (DW), Enterprise Data Certifications: None Experience: 10 + years of related experience US ...

Showing results 21-40

Data Science information

See West Virginia salary details

$29K

$95K

$152.1K

How much do data science jobs pay per year?

As of Aug 16, 2026, the average yearly pay for data science 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.

Is a data scientist in high demand?

Yes, data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.

What are the most commonly searched types of Data Science jobs in West Virginia?

The most popular types of Data Science jobs in West Virginia are:

What are popular job titles related to Data Science jobs in West Virginia?

For Data Science jobs in West Virginia, the most frequently searched job titles are:

What cities in West Virginia are hiring for Data Science jobs?

Cities in West Virginia with the most Data Science job openings:

Infographic showing various Data Science job openings in West Virginia as of August 2026, with employment types broken down into 90% Full Time, and 10% Part Time. Highlights an 100% In-person job distribution, with an average salary of $95,020 per year, or $45.7 per hour.

Senior Data Engineer

AmeriSave Mortgage Corp.

Charleston, WV

$98K - $133K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 10 days ago


Job description

AmeriSave Mortgage Corporation has set the standard in online mortgage lending with over $130 billion in funded loan volume. As one of the top-rated, largest privately-owned online mortgage lenders in the nation, our mission is to deliver beneficial, responsible home lending solutions with unwavering integrity, dedication and excellence. As a leading mortgage lender, we pride ourselves on our innovative approach and commitment to customer satisfaction.

Our employees are the driving force behind our success. We believe in the power of a dynamic and talented workforce and creating an environment where your contributions are not just recognized, they’re celebrated. Your success is our success, and we are seeking skilled professionals who are ready to bring their A-game, exceed benchmarks and enhance the overall excellence of AmeriSave, while also growing and advancing their careers.

At AmeriSave, we're one team with one shared dream - to be the best.  Let’s redefine excellence together!

What We’re Looking For:

We are seeking a highly skilled Senior Data Engineer to join the Enterprise Intelligence department at AmeriSave Mortgage. This role will be responsible for designing, developing, and maintaining a best-in-class enterprise data warehouse to support advanced analytics, data science, and Artificial Intelligence activities throughout the company. The Senior Data Engineer will report directly to the Senior Vice President of Enterprise Intelligence.

Observability & Monitoring 

  • Own the control tower for database health across the Azure SQL estate — standing up and maintaining monitoring through database watcher, Azure Monitor metrics and alerts, Query Store, DMVs, and Log Analytics / KQL.
  • Establish wait-statistics, file-I/O, and resource (DTU/vCore) baselines per workload, defining what "normal" looks like per workload and per time-of-day.
  • Define and continuously tune Azure Monitor alert rules and action groups (blocking, deadlocks, long-running queries, resource saturation) against those baselines so alarms stay trusted and acted upon — alerting on statistical deviation rather than arbitrary thresholds.

What You’ll Do:

  • Design, develop, and maintain robust enterprise data warehouse solutions that support data science, artificial intelligence, and business intelligence requirements.
  • Architect scalable ETL/ELT pipelines to efficiently transform raw data into structured, analytics-ready formats.
  • Build and manage API integrations, including hands-on API development.
  • Utilize T-SQL and Azure Data Factory to create, optimize, and manage data integration workflows.
  • Use Microsoft Fabric notebooks for transformation and orchestration where appropriate, leveraging Lakehouse and Warehouse for supplemental storage.
  • Ensure high data quality, integrity, and performance through meticulous query tuning and process optimization.
  • Collaborate with data scientists, software developers, business intelligence teams, and stakeholders to develop and deploy data solutions that meet business needs.
  • Translate business requirements into technical solutions and coordinate smoothly between engineering and other teams.
  • Lead the creation of scalable, reliable data models and optimize them for performance and usability.
  • Drive continuous improvement in data engineering processes and practices to keep them efficient and aligned with industry best practices.
  • Monitor system performance and proactively implement improvements to maximize efficiency and scalability.
  • Troubleshoot and resolve data-related issues to ensure reliable data delivery.

What You’ll Need:

  • This role is ideal for someone who thrives in a dynamic, fast-paced environment, enjoys solving complex data problems, and is passionate about driving innovation in data engineering.
  • 5+ years of hands-on experience in data warehousing, data engineering, or a similar role.
  • Extensive experience with T-SQL, including advanced query development and performance tuning.
  • 5+ years as a SQL Server / Azure SQL DBA — performance tuning, index and statistics management, execution-plan analysis, and proactive capacity planning.
  • Proficiency with pipeline development and configuration using Azure Data Factory (ADF).
  • Working familiarity with Microsoft Fabric (notebooks and pipelines for transformation, Lakehouse, and Warehouse)
  • Expertise in Python for data engineering tasks, including data manipulation and workflow management.
  • Strong understanding of data modeling, data architecture, and best practices in data governance.
  • Experience handling sensitive/PII data and supporting data quality and governance in a regulated, financial-services environment.
  • Experience preparing clean, analytics- and ML-ready datasets to support data science and AI workloads.
  • Excellent problem-solving skills and the ability to work independently as well as collaboratively.
  • Strong communication skills to effectively liaise with both technical teams and non-technical stakeholders.

**Please note that the compensation information that follows is a good faith estimate for this position only and is provided pursuant to the Colorado Equal Pay for Equal Work Act and Equal Pay Transparency Rules. It is estimated based on what a successful Colorado applicant might be paid. It assumes that the successful candidate will be in Colorado or perform the position from Colorado. Similar positions located outside of Colorado will not necessarily receive the same compensation. ** 

Compensation: 

Annual compensation for this position generally ranges from $100,000 - $170,000. 

Benefits: 

·         401(k) 

·         Dental insurance 

·         Disability insurance 

·         Employee discounts 

·         Health insurance 

·         Life insurance 

·         Paid time off 

·         12 paid holidays per year 

·         Paid training 

·         Referral program 

·         Vision insurance 

Supplemental pay types: 

·         Bonus 

·         Referral bonuses 

AmeriSave is an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

California Consumer Privacy Act Disclosure Acknowledgment 

Employment Applicants, New Hires, and Employees Residing in California 

AmeriSave Mortgage Corporation’s Privacy Policy Statement (“Policy”) can be reviewed here: www.amerisave.com/privacy-policy 

AmeriSave Mortgage Corporation’s California Consumer Privacy Act (“CCPA”) Recruitment Disclosure can be reviewed here: https://www.amerisave.com/ccpa-recruitment-disclosure/ 

When AmeriSave’s Human Resources Department makes future requests for personal information, the same Policy is applicable. By applying, you understand this acknowledgment covers current and future personal information requests. You also acknowledge the business purpose of the personal information collected and that future requests may occur while applying for a position at AmeriSave and/or during employment, if applicable.