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Data Mining Online Jobs in Reston, VA (NOW HIRING)

Data Scientist, Lead

Washington, DC · On-site

$120 - $190/hr

Perform statistical analysis, apply data mining techniques, and build high quality prediction systems. The successful candidate should be skilled in data visualization and use of graphical ...

Data Scientist

Springfield, VA · On-site

$92.30 - $166.85/hr

Programming (Python/Pig/Java/JS/SQL/R), spatial analysis, data mining, database structures, visualization. * Statistical/mathematical modeling. * Experience managing data science projects, data ...

Overview BigBear.ai is seeking a Data Scientist to conduct data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis using scientific ...

Overview BigBear.ai is seeking a Data Scientist to conduct data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis using scientific ...

Data analysis and predictive analytics such as statistics, rule-based systems, regression and rule-based systems, regression, and data mining systems, and deploying such systems Job Requirements Job ...

Data Scientist - Mid

Washington, DC · On-site

$110K - $122K/yr

Conduct data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis, and uses scientific techniques to correlate data into graphical, written ...

Junior Data Analyst

Reston, VA · On-site

$60 - $85/hr

Conducting data analysis and predictive analytics such as statistics, rule‑based systems, regression, and data mining systems, and deploying such systems. Qualifications * Minimum 2-3 years in a ...

Data Scientist - Mid

Washington, DC · On-site

$140K - $155K/yr

Conduct data analytics, data mining, exploratory analysis, predictive analysis, and statistical analysis, and uses scientific techniques to correlate data into graphical, written, visual and verbal ...

Data Scientist - Mid

Washington, DC · On-site

$140K - $155K/yr

Conduct data analytics, data mining, exploratory analysis, predictive analysis, and statistical analysis, and uses scientific techniques to correlate data into graphical, written, visual and verbal ...

Showing results 21-40

Data Mining Online information

What is data mining in an online context?

Data mining online refers to the process of using algorithms and statistical methods to analyze large sets of digital data collected from the internet, such as website activity, social media interactions, or online transactions. The goal is to discover patterns, trends, and useful information that can help businesses make informed decisions, improve customer experiences, or detect fraud. Online data mining often involves the use of specialized software and tools to extract and process data from various online sources efficiently.

What are some common challenges faced by professionals working in data mining online, and how can they be addressed?

Professionals in online data mining often encounter challenges such as handling large, unstructured datasets and ensuring data privacy and security. Working remotely, they must also stay updated with rapidly evolving tools and algorithms. Effective solutions include leveraging cloud-based platforms for scalable processing, collaborating closely with IT and data security teams, and participating in regular upskilling through webinars and online courses to maintain technical proficiency.

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

To thrive as a Data Mining Specialist, you need strong analytical skills, a solid background in statistics, and proficiency in programming languages like Python or R, often supported by a degree in computer science, statistics, or a related field. Familiarity with data mining tools such as RapidMiner, Weka, or SAS, as well as database management systems and machine learning frameworks, is typically required. Attention to detail, problem-solving abilities, and effective communication skills help you interpret complex data and present actionable insights to stakeholders. These skills and qualities are crucial for extracting valuable patterns from large datasets and driving data-driven decision-making in organizations.

What is the difference between Data Mining Online vs Data Analyst?

AspectData Mining OnlineData Analyst
Required CredentialsBachelor's in CS, Statistics, or related; certifications like Certified Data Mining SpecialistBachelor's in Data Science, Statistics, or related; often similar certifications
Work EnvironmentPrimarily remote, project-based, often freelance or contractOffice or remote, ongoing analysis roles within organizations
Industry UsageUsed across tech, e-commerce, marketing for extracting insights from online dataUsed in finance, healthcare, marketing for interpreting data trends

Data Mining Online focuses on extracting patterns from online data sources, often in a freelance or remote setting. Data Analysts interpret data within organizations to inform decisions. While both roles require similar skills and credentials, Data Mining Online emphasizes online data sources and often involves project-based work, whereas Data Analysts typically work within a company's data team on ongoing analysis.

How do you become a data mining online?

To become a data miner online, you typically need a background in data analysis, statistics, or computer science, along with skills in programming languages like Python or R. Gaining experience with data mining tools and techniques, completing relevant online courses or certifications, and building a portfolio of projects can help establish expertise in the field.

What are the most commonly searched types of Data Mining jobs in Reston, VA?

The most popular types of Data Mining jobs in Reston, VA are:

What are popular job titles related to Data Mining Online jobs in Reston, VA?

For Data Mining Online jobs in Reston, VA, the most frequently searched job titles are:

What job categories do people searching Data Mining Online jobs in Reston, VA look for?

The top searched job categories for Data Mining Online jobs in Reston, VA are:

What cities near Reston, VA are hiring for Data Mining Online jobs?

Cities near Reston, VA with the most Data Mining Online job openings:

Infographic showing various Data Mining Online job openings in Reston, VA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.

Senior Data Scientist (OBI Analytic Efficiency Enablement) - OBI with Security Clearance

CELESTAR CORPORATION

Reston, VA • On-site

Other

Medical, Dental, Life, Retirement, PTO

Re-posted 11 hours ago


Key responsibilities

  • Conducts data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis to support DIA initiatives.

  • Builds AI tools and machine learning-based processes, such as recommendation engines or automated lead scoring systems, to automate analytic tasks.

  • Collaborates with team members to develop and refine advanced analytic techniques, including leveraging novel technologies like large language models and natural language processing.


Job description

Celestar Corporation is seeking a Senior Data Scientist (OBI Analytic Efficiency Enablement) to support The Defense Intelligence Agency ( DIA) under the Object Based Intelligence and Quality Assurance (OBIQUA) task order. The primary place of performance will be at DIA Facilities across the National Capital Region (NCR). If interested and meet the qualifications, we encourage you to apply for this rewarding and impactful opportunity. ANTICIPATED AWARD: TBD ANTICIPATED START: TBD PERIOD OF PERFORMANCE: 1 Base Year + 4 Option Years LOCATION: DIA Facilities across the National Capital Region (NCR) CLEARANCE REQUIREMENT: Active TS/SCI About Us: Celestar, a proud Veteran-Owned company, offers highly competitive salaries and benefits. Our comprehensive benefits package includes company-paid employee and family dental insurance, employee health insurance, life insurance, and disability coverage. Additionally, we provide a 401(k)-retirement plan with company matching, paid holidays, and personal time off. Responsibilities: This opportunity will support multiple DIA initiatives, including the Machine-Assisted Rapid-Repository System (MARS), Object Management Services (OMS), and Object-Based Intelligence (OBI). • The Senior Data Scientist (OBI Analytic Efficiency Enablement) Conducts data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis, and uses scientific techniques to correlate data into graphical, written, visual and verbal narrative products, enabling more informed analytic decisions. • Proactively retrieves information from various sources, analyzes it for better understanding about the data set, and builds AI tools that automate certain processes. • Duties typically include: creating various ML-based tools or processes, such as recommendation engines or automated lead scoring systems. Performs statistical analysis, applies data mining techniques, and builds high quality prediction systems. • Should be skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI-) and Tableau; major data science languages, such as R and Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms. • Should have prior experience with large data multi INT analytics, ML, and automated predictive analytics. • Possesses a professional or graduate certificate in data science from a university, major online learning platform (all business for Data Scientists at any experience level). • Designs, develops, and evaluates leading-edge algorithmic intelligence concepts, practices, and technologies for implementation into OBI via all-source analysis tradecraft, assessments, production, and dissemination. • Proposes advanced statistical or mathematical techniques and methodology that may permit identification and evaluation of alternatives, assists in model formulation or experimental test design, and shares jointly in team responsibility for development of advanced analytic techniques and assessments. • Collaborate with team members to develop and refine exploratory efforts leveraging novel technologies (e.g. large language models, natural language processing, machine learning) to automate ontologies and associated components to ensure semantic accuracy, relevance, and interoperability with existing knowledge modeling and knowledge graph capabilities. • Evaluates data science, artificial intelligence, and other advanced analytic methods for risks, biases, and limitations that would distort conclusions. • Collaborate with team members to develop and refine semantic data retrieval and reasoning across knowledge graphs through development and optimization of data queries via multiple protocols (e.g. GraphQL, SPARQL, SHACL, SQL). • Conducts continuous independent research on methods of analysis in government, industry, and academia to keep abreast of the state of the art, keeps senior leadership apprised of the advances and applicability to programs. • Utilizes in-depth knowledge of relevant theories, techniques, procedures and processes to investigate, prototype, and evaluate technologies to improve all-source intelligence analysis. • Collaborate with team members to develop and refine exploratory efforts leveraging novel technologies (e.g. large language models, natural language processing, machine learning) to support and automate entity recognition and extraction, summarization, in accordance with analytic tradecraft standards, to enhance advanced analytic integration for OBI efforts. • Performs research studies to understand the process of augmenting or automating all source analytic processes using various computer models. • Provides incremental enhancements to tools, capabilities, processes, and methods. • Possesses in-depth knowledge and experience in using data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis, and scientific techniques to correlate data into graphical, written, visual and verbal narrative products, enabling more informed analytic decisions. • Writes either R or Python scripts to drive data science workflows, have experience using SQL, and managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms. • Possesses prior experience with large data, spatial data, Multi-INT analytics, ML, and automated predictive analytics. • Works with ambiguous information, deconstruct key questions, leverage spatial data, exploit application programming interfaces, suggest methodologies, develop data schemas to structure observations. This requires working knowledge of coding and scripting, information science, mathematics, machine learning, visual analytic modeling tools, and relevant Standard Operating Procedures (SOPs) to create repeatable, widely applicable procedures to support all-source intelligence analysis and production. • Creates and works in distributed analytic environments, scaling algorithms to work on increasingly large and complex datasets that are larger than RAM. • Serves as the primary POC for data science expertise, ensuring tradecraft compliance and analytic standards as it relates to data science techniques on the contract. • Provides advice on emerging data science methods, tools, algorithms, training, or requirements to advance DIA's analytic edge in its use of data science. • Works with DIA vendors and the software developers to implement distributed algorithms to work on increasingly large and complex data sets. • Review and evaluate OBI documentation submitted by advanced analytic (AA) owners to ensure compliance with tradecraft standards and adherence to best practices in AI system development and deployment. • Assess OBI documentation for completeness, accuracy, and thoroughness, and provide detailed feedback to owners and developers. • Provide consultation and guidance to data and AA owners, developers, and stakeholders on OBI governance and knowledge modeling, including best practices for system development, testing, and deployment. • Assist analytic methodologists and AA owners in translating technical documentation into analytic tradecraft compliant language. • Collaborate with team members to identify and implement practices for responsible AI development, including but not limited to bias detection, hallucination recognition, prompt fairness testing, adherence to analytic tradecraft standards and security policies. • Collaborate with stakeholders to develop, implement, and refine best practices for translating technical documentation into tradecraft compliant language. • Review and edit translated documentation to ensure accuracy, completeness, and adherence to tradecraft standards. • Collaborate with the team members to develop and implement testing methodologies for system validation and evaluation leveraging qualitative and quantitative metrics (e.g. consistency, method or reasoning completeness, coverage of method or model for proposed solution). • Conduct audits to ensure compliant use of systems for approved use-cases in all source analysis. • Develop and maintain a repository of audit findings and recommendations to facilitate knowledge sharing and best practices across the organization. • Design and execute TEVV protocols to evaluate the performance, robustness, and fairness of systems in all source analysis contexts. • Develop and apply statistical models and methods to analyze TEVV results and identify areas for improvement. • Collaborate with stakeholders to develop and implement corrective actions to address TEV findings. • Develop and track performance metrics to evaluate the effectiveness of systems in all source analysis. • Analyze and interpret performance metrics to identify trends, patterns, and areas for improvement. • Collaborate with stakeholders to develop and implement data-driven decision-making processes to inform system development and improvement. • Develop and refine methodologies for evaluating system performance, robustness, and fairness in all source analysis contexts. • Collaborate with stakeholders to develop and implement best practices for system development, testing, and deployment. • Supports capability development by contributing, editing, and storing code in Government owned/controlled source version control repositories. Required qualifications/skills: • Minimum 12 years of experience related to the specific labor category with at least a portion of the experience within the last 2 years with a master's degree. -OR- • A minimum of 17 years of experience related to the specific labor category with at least a portion of the experience within the last 2 years with a bachelor's degree. • Must have at least 8 years of experience in AI implementation, advanced degree in computer science, data science, or related field. • Must have expertise in AI algorithms,