Be Challenged and Make a Difference
In a world of technology, people make the difference. We believe if we invest in great people, then great things will happen. At AnaVation, we provide unmatched value to our customers and employees through innovative solutions and an engaging culture.
Required Qualifications
Clearance: U.S. Citizen; TS/SCI w/ CI Poly
Education: Bachelor's degree in Computer Science, Data Science, Information Systems, Mathematics, Statistics, Super Intelligence/Machine Learning or a related field, or equivalent relevant experience.
Certification: DoD 8140/8570 IAT Level II (GSEC, SSCP) or equivalent credential
Location: Full time on-site at Annapolis Junction, Maryland.
Experience and knowledge
- 10+ years of experience across data science, advanced analytics, machine learning engineering, quantitative
- analysis, or related technical disciplines.
- Expert proficiency in Python for data analysis, algorithm development, machine learning, or analytical
- application development.
- Demonstrated experience applying statistical analysis, machine learning, predictive modeling, or other advanced
- analytical techniques to complex data and mission or business problems.
- Demonstrated experience developing, evaluating, and refining analytical algorithms, predictive models, or
- machine learning solutions.
Demonstrated experience using PyTorch to develop, train, evaluate, or implement machine learning models.
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- Demonstrated experience with Neo4j or comparable knowledge graph technologies, including graph data
- modeling, querying, or graph-based analysis.
- Demonstrated experience developing data science applications, analytical prototypes, or interactive analytical
- interfaces using Streamlit or equivalent hands-on Streamlit experience.
- Demonstrated experience using Git for version control and JIRA for technical work tracking, collaboration, or
- project execution.
- Experience working with complex, heterogeneous datasets, including structured and unstructured data, and
- developing methods to improve data quality, integration, interoperability, or analytical usability.
- Demonstrated understanding of model evaluation, validation, performance measurement, and the limitations of
- statistical and machine learning approaches.
- Demonstrated ability to translate complex mission requirements into analytical approaches, technical solutions,