Prescient Edge
Mid. Data Scientist (OBI Analytic Efficiency Enablement)
Prescient Edge, Virginia, Minnesota, United States, 55792
Mid. Data Scientist (OBI Analytic Efficiency Enablement) - (2684)
Job Title
Mid. Data Scientist (OBI Analytic Efficiency Enablement)
Location
NCR, US (Primary)
Category
Job Type
Full-Time
Staff
Education
Bachelor's Degree
Travel
None
Security Clearance Required
TS/SCI with CI Polygraph
Job Description
Prescient Edge is seeking a
Mid Data Scientist
to support a federal government client.
Please note that the availability of this position is contingent upon contract award.
Mid. Data Scientist (OBI Analytic Efficiency Enablement)
At
Prescient
Edge
, we believe that acting with integrity and serving our employees is the key to everyone's success. To that end, we provide employees with a best‑in‑class benefits package that includes:
A competitive salary with performance bonus opportunities.
Comprehensive healthcare benefits, including medical, vision, dental, and orthodontia coverage.
A substantial retirement plan with no vesting schedule.
Career development opportunities, including on‑the‑job training, tuition reimbursement, and networking.
A positive work environment where employees are respected, supported, and engaged.
Description:
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.
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 software developers to implement distributed algorithms to work on increasingly large and complex data sets.
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, Al, 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 appraising 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 that leverage novel technologies (e.g., large language models, natural language processing, machine learning) to support and automate entity recognition and extraction, as well as 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, ML, 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 software developers to implement distributed algorithms to work on increasingly large and complex datasets.
Review and evaluate OBI documentation submitted by advanced analytic (AA) owners to ensure compliance with tradecraft standards and adherence to best practices in Al 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 date 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 Al 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 för 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 TEVV 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.
Job Requirements
Desired experiences:
At least 8 years of experience conducting analysis relevant to the specific labor category with at least a portion of the experience within the last 2 years.
Desired education:
Bachelor’s degree in an area related to the labor category from a college or university accredited by an agency recognized by the U.S. Department of Education.
An additional 4 years of experience in the specific labor category, for a total of 12 years of experience in the specific labor category, may be substituted for a bachelor’s degree.
Security Clearance:
Security clearance required TS/SCI with CI POLY or the ability to obtain CI POLY.
Location:
NCR to include Maryland and Virginia.
Prescient Edge is a Veteran‑Owned Small Business (VOSB) founded as a counterintelligence (CI) and Human Intelligence (HUMINT) company in 2008. We are a global operations and solutions integrator delivering full‑spectrum intelligence analysis support, training, security, and RD&E support solutions to the Department of Defense and throughout the intelligence community. Prescient Edge is an Equal Opportunity Employer (EEO). All applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic that is protected by law. We strive to foster equity and inclusion throughout our organization because we believe that diversity of thought is critical for creating a safe and engaging work environment while also enabling the organization’s success.
#J-18808-Ljbffr
Mid. Data Scientist (OBI Analytic Efficiency Enablement)
Location
NCR, US (Primary)
Category
Job Type
Full-Time
Staff
Education
Bachelor's Degree
Travel
None
Security Clearance Required
TS/SCI with CI Polygraph
Job Description
Prescient Edge is seeking a
Mid Data Scientist
to support a federal government client.
Please note that the availability of this position is contingent upon contract award.
Mid. Data Scientist (OBI Analytic Efficiency Enablement)
At
Prescient
Edge
, we believe that acting with integrity and serving our employees is the key to everyone's success. To that end, we provide employees with a best‑in‑class benefits package that includes:
A competitive salary with performance bonus opportunities.
Comprehensive healthcare benefits, including medical, vision, dental, and orthodontia coverage.
A substantial retirement plan with no vesting schedule.
Career development opportunities, including on‑the‑job training, tuition reimbursement, and networking.
A positive work environment where employees are respected, supported, and engaged.
Description:
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.
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 software developers to implement distributed algorithms to work on increasingly large and complex data sets.
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, Al, 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 appraising 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 that leverage novel technologies (e.g., large language models, natural language processing, machine learning) to support and automate entity recognition and extraction, as well as 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, ML, 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 software developers to implement distributed algorithms to work on increasingly large and complex datasets.
Review and evaluate OBI documentation submitted by advanced analytic (AA) owners to ensure compliance with tradecraft standards and adherence to best practices in Al 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 date 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 Al 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 för 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 TEVV 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.
Job Requirements
Desired experiences:
At least 8 years of experience conducting analysis relevant to the specific labor category with at least a portion of the experience within the last 2 years.
Desired education:
Bachelor’s degree in an area related to the labor category from a college or university accredited by an agency recognized by the U.S. Department of Education.
An additional 4 years of experience in the specific labor category, for a total of 12 years of experience in the specific labor category, may be substituted for a bachelor’s degree.
Security Clearance:
Security clearance required TS/SCI with CI POLY or the ability to obtain CI POLY.
Location:
NCR to include Maryland and Virginia.
Prescient Edge is a Veteran‑Owned Small Business (VOSB) founded as a counterintelligence (CI) and Human Intelligence (HUMINT) company in 2008. We are a global operations and solutions integrator delivering full‑spectrum intelligence analysis support, training, security, and RD&E support solutions to the Department of Defense and throughout the intelligence community. Prescient Edge is an Equal Opportunity Employer (EEO). All applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic that is protected by law. We strive to foster equity and inclusion throughout our organization because we believe that diversity of thought is critical for creating a safe and engaging work environment while also enabling the organization’s success.
#J-18808-Ljbffr