Prescient Edge is seeking a Sr. Data Scientist (OBI Analytic Efficiency Enablement) to support a Federal Government client. Please note that the availability of this position is contingent upon contract award.
Sr. Data Scientist (OBI Analytic Efficiency Enablement) Benefits:
At Prescient Edge, we believe that acting with integrity and serving our employees is the key to everyones 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. • Performing statistical analysis, applies data mining techniques, and builds high quality prediction systems. • Being 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. • Having prior experience with large data Multi-INT analytics, ML, and automated predictive analytics. • Providing incremental enhancements to tools, capabilities, processes, and methods. • Possessing 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.
Key Responsibilities:
• Writing 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. • Possessing prior experience with large data, spatial data, Multi-INT analytics, ML, and automated predictive analytics. • Working 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. • Creating and working in distributed analytic environments, scaling algorithms to work on increasingly large and complex datasets that are larger than RAM. • Serving as the primary POC for data science expertise, ensuring tradecraft compliance and analytic standards as it relates to data science techniques on the contract. • Providing advice on emerging data science methods, tools, algorithms, training, or requirements to advance DIAs analytic edge in its use of data science. • Working with DIA vendors and software developers to implement distributed algorithms to work on increasingly large and complex datasets.
OBI Responsibilities:
• 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. • Collaborating 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. • Evaluating data science, Al, and other advanced analytic methods for risks, biases, and limitations that would distort conclusions. • Collaborating 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). • Conducting 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. • Utilizing in-depth knowledge of relevant theories, techniques, procedures and processes to investigate Prototype, and evaluate technologies to improve all-source intelligence analysis. • Collaborating 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. • Performing research studies to understand the process of augmenting or automating all source analytic processes using various computer models. • Providing incremental enhancements to tools, capabilities, processes, and methods. • Possessing 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.
Additional Responsibilities:
• 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. • Providing 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. • Assisting analytic methodologists and AA owners in translating technical documentation into analytic tradecraft compliant language. • Collaborating 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. • Collaborating with stakeholders to develop, implement, and refine best practices for translating technical documentation into tradecraft compliant language. • Reviewing and editing translated documentation to ensure accuracy, completeness, and adherence to tradecraft standards. • Collaborating 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). • Conducting audits to ensure compliant use of systems for approved use-cases in all source analysis. • Developing and maintaining a repository of audit findings and recommendations to facilitate knowledge sharing and best practices across the organization. • Designing and executing TEVV protocols to evaluate the performance, robustness, and fairness of systems in all source analysis contexts. • Developing and applying statistical models and methods to analyze TEVV results and identify areas for improvement. • Collaborating with stakeholders to develop and implement corrective actions to address TEVV findings. • Developing and tracking performance metrics to evaluate the effectiveness of systems in all source analysis. • Analyzing and interpreting performance metrics to identify trends, patterns, and areas for improvement. • Collaborating with stakeholders to develop and implement data-driven decision-making processes to inform system development and improvement. • Developing and refining methodologies for evaluating system performance, robustness, and fairness in all source analysis contexts. • Collaborating with stakeholders to develop and implement best practices for system development, testing, and deployment. • Supporting capability development by contributing, editing, and storing code in Government owned/controlled source version control repositories.