Senior Data Scientist

2 weeks ago

Charlottesville, United States Valorous Inc. Full time
Senior Data Scientist

Location: Charlottesville, VA

Your Impact:

Valorous is seeking for Senior Data Scientist to support its federal client in Charlottesville, VA.

The Program is a premier program in the industry that advances the use of tactical and strategic Identity Intelligence tradecraft to inform decision-makers, from ground force commanders to international partners and national security policymakers. Our employees lead the Intelligence community in providing superior Identity Intelligence analysis and developing innovative data-driven solutions, supporting the customer through intelligence analysis and tradecraft proliferation.

Responsibilities:
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.

Responsibilities include:

- Collaborates with stakeholders within the organization to identify opportunities for leveraging data to drive analytical solutions.
- Mines and analyzes data from databases to drive optimization and improvement of product development, analytical techniques, and analytical assessments.
- Develops, tests and verifies TTPs for coordinating flow of information.
- Develops processes and tools to monitor and analyze model performance and data accuracy.
- Trains front-end users of knowledge management tools.
- Coordinates with various functional teams to implement models and monitor outcomes.
- Creates predictive modeling to increase and optimize customer experiences. #divergent

Requirements:

- Clearance Required: TS/SCI

- Proficiency in at least one of the following languages: Python, R, Java, C , as applied to programming and manipulation of data.
- Demonstrated experience working with one or more database structures (e.g. relational, noSQL, graph). Such expertise should include experience with database retrieval methods (e.g. SQL, database specific queries, APIs).
- Experience creating and using advanced machine learning algorithms and statistics, regression, simulation, scenario analysis, modeling, clustering, decision trees, and neural networks.
- Knowledge and experience in statistical and data mining techniques and social network analysis.
- Knowledge and understanding of Department of Defense (DoD) and Intelligence Community (IC) operations, data infrastructure and architecture.
- Familiar with DoD/IC activities, functions and organizational structures.
- Familiar with cloud services as applied in the DoD and IC.
- Experience in simplification and optimization of data automation workflows; streamlining of extract-transform-load (ETL) operations.
- Certification as an IT architect or enterprise architect from the Open Group, FEAC, or other industry recognized IT architecture certification program.
- Knowledge of IT related disciplines: Software Development Life Cycle (SDLC), including a basic understanding of various SDLC methodologies such as agile and waterfall and their appropriate usage.
- Knowledge of modeling approaches: Unified Modeling Language (UML), Business Process modeling, and Data Modeling.

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