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Temporary Data Scientist Machine Learning Jobs in Virginia

KDA Consulting Inc

Data Scientist

Chantilly, VA · On-site

Machine Learning & AI Development * Design, develop, and deploy machine learning models to solve complex mission problems * Build predictive and prescriptive analytics solutions to support ...

KDA Consulting Inc

Data Scientist

Mclean, VA · On-site

Machine Learning & AI Development * Design, develop, and deploy machine learning models to solve complex mission problems * Build predictive and prescriptive analytics solutions to support ...

KDA Consulting Inc

Data Scientist

Herndon, VA · On-site

Machine Learning & AI Development * Design, develop, and deploy machine learning models to solve complex mission problems * Build predictive and prescriptive analytics solutions to support ...

KDA Consulting Inc

Data Scientist

Chantilly, VA · On-site

Machine Learning & AI Development * Design, develop, and deploy machine learning models to solve complex mission problems * Build predictive and prescriptive analytics solutions to support ...

Cmu

Data Scientist

Arlington, VA

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and artificial intelligence to help our government and industry clients research and solve cybersecurity ...

VTG

Data Scientist

Chantilly, VA · On-site

A Data Scientist represents an effective arbiter of strong technical knowledge and clear ... May use machine learning and statistical approaches based on the analysis of the dataset. May ...

VTG

Data Scientist

Chantilly, VA

A Data Scientist represents an effective arbiter of strong technical knowledge and clear ... May use machine learning and statistical approaches based on the analysis of the dataset. May ...

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All JobsTemporary Data Scientist Machine Learning JobsTemporary Data Scientist Machine Learning Jobs in Virginia

Temporary Data Scientist Machine Learning information

What is the difference between Temporary Data Scientist Machine Learning vs Temporary Data Analyst?

AspectTemporary Data Scientist Machine LearningTemporary Data Analyst
Required CredentialsBachelor's/Master's in Data Science, Computer Science, or related fields; knowledge of ML algorithmsBachelor's in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentProject-based, collaborative teams, tech-focused companiesBusiness units, reporting teams, data-driven departments
Employer & Industry UsageTech firms, finance, healthcare, e-commerceRetail, marketing, finance, consulting

Temporary Data Scientist Machine Learning roles focus on developing and deploying machine learning models, requiring advanced analytics skills. Temporary Data Analysts primarily interpret data, generate reports, and support decision-making. While both roles involve data handling, Data Scientists with ML expertise work on predictive modeling, whereas Data Analysts focus on descriptive analytics. The choice depends on the project needs and skill requirements.

What does a Temporary Data Scientist specializing in Machine Learning do?

A Temporary Data Scientist specializing in Machine Learning is responsible for designing, building, and deploying machine learning models to analyze data and generate insights, but works on a contract or short-term basis. Their duties often include data preprocessing, model selection and validation, and communicating results to stakeholders. They may also be tasked with automating processes, cleaning large datasets, and collaborating with other teams to implement solutions. The temporary nature of the job means they often focus on specific projects or provide support during peak periods.

What are the key skills and qualifications needed to thrive as a Temporary Data Scientist Machine Learning, and why are they important?

To thrive as a Temporary Data Scientist Machine Learning, you generally need a strong background in statistics, programming (Python or R), and experience with machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with data visualization tools (like Tableau), machine learning libraries (such as scikit-learn, TensorFlow, or PyTorch), and version control systems (e.g., Git) is typically required. Strong problem-solving abilities, adaptability, and effective communication are crucial soft skills for collaborating with teams and translating technical findings to stakeholders. These skills ensure that temporary data scientists can quickly contribute actionable insights, drive data-driven decisions, and add value within a limited time frame.

What are some typical projects or tasks a temporary Data Scientist specializing in machine learning might work on?

As a temporary Data Scientist focusing on machine learning, you can expect to work on short-term, high-impact projects such as building predictive models, cleaning and preparing data, or developing automated analytics solutions. You may be brought in to support ongoing initiatives, provide expertise for a specific project phase, or help accelerate a backlog of tasks. Collaboration is common, and you'll likely work closely with data engineers, business analysts, and domain experts to understand requirements and deliver actionable insights within tight deadlines. This role offers exposure to diverse datasets and tools, and is an excellent opportunity to rapidly expand your experience and network.
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Temporary Data Scientist Machine Learning jobs near you

Data Scientist

KDA Consulting Inc

Chantilly, VA • On-site

Full-time

Posted 22 days ago

Job description

KDA Consulting Inc. is seeking a highly skilled Data Scientist with AI/ML expertise to support mission-critical programs within the Intelligence Community (IC). This role will focus on leveraging advanced analytics, machine learning, and artificial intelligence to extract insights from large, complex datasets and support data-driven decision-making.
The ideal candidate will have a strong foundation in statistical analysis, machine learning model development, and data visualization, along with the ability to translate complex findings into actionable insights for both technical and non-technical stakeholders.
Machine Learning & AI Development
  • Design, develop, and deploy machine learning models to solve complex mission problems
  • Build predictive and prescriptive analytics solutions to support operational and strategic decision-making
  • Evaluate model performance and continuously improve algorithms through testing and tuning

Data Analysis & Exploration
  • Analyze large, structured and unstructured datasets to identify trends, patterns, and anomalies
  • Perform data cleansing, feature engineering, and transformation to prepare data for modeling
  • Apply statistical techniques to validate hypotheses and support analytical findings

Data Visualization & Communication
  • Develop dashboards, visualizations, and reports using tools such as Tableau, Power BI, or Python visualization libraries
  • Communicate insights and recommendations clearly to both technical teams and senior leadership
  • Translate complex analytical results into actionable business or mission outcomes

Model Deployment & Integration
  • Collaborate with data engineers and software developers to operationalize models into production environments
  • Integrate machine learning solutions into enterprise systems and workflows
  • Support cloud-based model deployment in environments such as AWS or Azure

Collaboration & Agile Delivery
  • Work closely with cross-functional teams including engineers, analysts, and mission stakeholders
  • Participate in Agile processes including sprint planning, stand-ups, and retrospectives
  • Contribute to continuous improvement of data science methodologies and processes

Requirements
Active TS/SCI W/ Polygraph Required.
Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field (or equivalent experience)
Strong experience in data science, machine learning, and statistical analysis
Proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
Experience analyzing and working with large-scale datasets
Strong understanding of statistical modeling, probability, and data analysis techniques
Experience with data visualization tools and communicating insights effectively
Strong problem-solving skills and ability to work in complex, mission-driven environments

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