Data Scientist

RADGOV INC
Washington, United States of America
7 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Washington, United States of America

Tech stack

Agile Methodologies
Artificial Intelligence
Data analysis
Continuous Integration
Data Visualization
Python
Machine Learning
Named Entity Recognition
Power BI
Software Deployment
Software Engineering
Tableau
Cloud Platform System
Flask
Generative AI
Containerization
Scikit Learn
Information Technology
Data Analytics
XGBoost
Spacy
Streamlit Framework
Programming Languages

Job description

The AI Lab operates as a small, agile team where practitioners are expected to move between research, development, and deployment activities. This position will contribute to strategy while doing hands-on technical work, building models, training systems, evaluating performance, and deploying solutions. The AI Lab collaborates closely with DCCA's Data Analytics and Risk and Surveillance sections, and coordinates with the Board's enterprise technology on infrastructure, governance, and compliance matters., AI/ML and Generative AI Development Deployment and Operations: Collaboration, Communication and Agile Practices Governance and Compliance Awareness

Requirements

At least six years of hands-on experience developing, deploying, and maintaining AI/ML applications within a large, professional, or academic organization Bachelor's degree in Computer Science, Data Science, Statistics, Machine Learning, or related technology field (Master's degree preferred) Expert proficiency in Python or R for data science development; experience with additional programming languages Production deployment experience: Demonstrated ability to build, deploy, and maintain AI/ML applications in cloud environments, including containerization and basic CI/CD practices Application development: Proficiency building interactive applications and dashboards using frameworks such as Streamlit, Dash, Flask, RShiny, or similar Data visualization: Strong experience creating visualizations and dashboards using Python/R libraries, Tableau, Power BI, or similar tools to communicate technical concepts to non-technical audiences AI/ML expertise: Advanced knowledge of machine learning, NLP (text normalization, Named Entity Recognition, POS tagging, word embeddings), and Generative AI technologies; experience with frameworks such as Scikit-learn, Spacy, XGBoost Statistical analysis: Advanced knowledge of statistical modeling, data analysis techniques, and problem-solving skills Ability to work independently and collaboratively, taking ownership of solutions from conception through production deployment

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