Principal Data Scientist

REI Systems-posted 2 months ago

Senior

Hybrid • Sterling, VA

Professional, Scientific, and Technical Services

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REI Systems' mission is to deliver reliable, innovative technology solutions that advance Federal clients' missions and exceed their expectations. Our technologists and consultants are passionate about solving complex challenges that impact millions of lives. We take a Mindful Modernization approach in delivering our services, including application modernization, grants management, case management systems, government data analytics, and advisory services. This approach, the REI Way, ensures mission impact by aligning our clients' strategic objectives with measurable outcomes through people, processes, and technology. We offer the same commitment to our employees by providing professional development, meaningful projects, and flexibility to spend time with family and friends. We believe employees are at their best when fulfilled in both their professional careers and their personal lives. Learn more at www.REIsystems.com. Employees voted REI Systems a Washington Post Top Workplace in 2015, 2016, 2018, 2020, 2021, 2022, 2023 and 2024! Have you ever wondered how the food you eat is deemed to be safe, or how pharmaceutical companies are inspected to ensure the drugs they produce meet FDA regulations? If so, we have a very large new program with the Food and Drug Administration (FDA) and would love to have you join us!

Collaborate directly with project stakeholders throughout the entire project lifecycle to define, design, and implement data-driven solutions.
Develop and implement advanced analytics models, machine learning algorithms, and data visualizations to provide actionable insights for clients.
Independently interface with client technical teams and business owners as needed during the design and implementation phases.
Supervise, mentor, and develop junior team members on data science methodologies and best practices.
Prepare data science business cases while working with domain experts and customers.
Support defining the AI strategy within a federal government agency.
Develop customized algorithms to solve analytical problems with incomplete data sets.
Build, train, validate, and test Machine Learning (ML) and Deep Learning (DL) models for various forms of data (structured and unstructured) and at different scales.
Perform data mining, pattern recognition, statistical and predictive modeling.
Design and implement solutions to automate manual processes at scale.
Conduct design of experiments and carry out statistical analysis.
Develop solutions for Natural Language Processing (NLP) and Computer Vision use cases.
Operationalize ML models using CI/CD best practices in the cloud environment.
Analyze time series data and create forecasting models.
Document, visualize, present analytic results to decision makers.
Provide informational briefings to explain methodologies and analytical findings to peers and customer stakeholders.
Investigate and implement new scientific methodologies to support analytic and big data requirements.
Find and recommend new uses for existing data sources; design, modify, and build new data processes; and build large, complex data sets.
Provide architecture analysis and design implementation with detailed technology roadmaps and transition planning and master plans as required.

7 plus years of experience with programming languages (such as Python, R), and statistical analysis with Python and R.
5 plus years of experience with machine learning and deep learning modelling (with frameworks such as TensorFlow, Keras, PyTorch, etc.).
Must have 5 years of experience with NLP and Computer Vision.
Experience in analysis, processing, tagging, and indexing unstructured, semi-structured, and structured data sets.
Experience with developing research designs, including formulating testable questions, identifying and defining key concepts and variables, and matching appropriate methods to problems.
Experience with data management, including cleaning and preparing data, and creating, structuring, and maintaining data sets.
Experience with incorporating data science capability into Stakeholder strategy.
Experience bridging data science strategy between leadership, IT, data scientists and other stakeholders.
Good understanding of Databases, SQL, Hadoop, Hive and/or MapReduce.
AWS or Azure experience is preferred.

Professional development opportunities
Flexibility to spend time with family and friends

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