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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Data Scientist - **Company:** Inc Washington - **Location:** Washington, DC, United States (Remote available) - **Experience:** Expert - **Contract:** Temporary to permanent - **Skills:** Microsoft Word, Agile Methodology, Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Data Analysis, Application Frameworks, JIRA, Microsoft Azure, Cloud Computing, Continuous Integration, Data Visualization, R (Programming Language), Monitoring of Systems, Information Extraction, IT Management, Python (Programming Language), Machine Learning, Named Entity Recognition, Performance Tuning, Power BI, Search Technologies, Software Deployment, Software Engineering, Tableau (Software), Management of Software Versions, Web Application Frameworks, Data Logging, Cloud Platform System, Captcha, Flask (Web Framework), Delivery Pipeline, Large Language Models, Prompt Engineering, Software Security, Model Validation, Generative AI, Cloudformation, Matplotlib, Containerization, Scikit Learn, Kubernetes, Xgboost, Plotly, Machine Learning Operations, Functional Programming, Text Analysis, Cloudwatch, Spacy, Streamlit Framework, Terraform, Document Classification, GPT, Docker - **Published:** July 22, 2026 - **Apply:** https://bryant-technologies.com/job_opening/senior-ai-data-scientist/ ## About the Role * Minimum 6 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 field (Master's degree preferred) * Expert proficiency in Python or R for data science development; experience with additional programming languages a plus * Production deployment experience: ability to build, deploy, and maintain AI/ML applications in cloud environments, including containerization and basic CI/CD practices * Proficiency building interactive applications and dashboards using frameworks such as Streamlit, Dash, Flask, or R Shiny * Strong experience creating visualizations and dashboards using Python/R libraries, Tableau, Power BI, or similar tools * Advanced knowledge of machine learning, NLP (Named Entity Recognition, POS tagging, word embeddings), and Generative AI technologies; experience with Scikit-learn, SpaCy, XGBoost * 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, * Generative AI & LLM application development: prompt engineering, RAG systems, fine-tuning, model evaluation * Cloud deployment: AWS, Kubernetes, containerization (Docker), CI/CD pipelines * Application frameworks: Streamlit, Dash, Flask, R Shiny * Data visualization: Plotly, Matplotlib, Seaborn, ggplot2, Tableau, Power BI * LLM APIs and frameworks: GPT, Llama, LangChain, LlamaIndex; vector databases and semantic search * AWS AI services: Amazon Bedrock, SageMaker, Comprehend, Rekognition, Transcribe * AWS deployment services: EC2, ECS, Lambda, S3, CloudWatch * Infrastructure as code: Terraform, CloudFormation * MLOps practices: model monitoring, versioning, automated retraining, and deployment pipelines * Responsible AI practices: bias detection, fairness evaluation, and model interpretability * Agile project tracking tools: Jira, Azure DevOps * Federal IT governance frameworks: FISMA, privacy requirements, and application security in regulated environments ## Description * Research, design, and develop machine learning and generative AI solutions, including proof-of-concept prototypes transitioning into production applications * Design and implement applications leveraging large language models (LLMs) for text analysis, summarization, information extraction, document classification, and workflow automation * Develop prompt engineering strategies and retrieval-augmented generation (RAG) systems to improve AI application performance * Build, deploy, and maintain AI/ML models in cloud environments (AWS, Kubernetes), managing end-to-end deployment independently or collaboratively * Develop interactive dashboards and analytical applications using Python frameworks (Streamlit, Dash, Flask) or R Shiny * Manage deployment pipelines including containerization (Docker), CI/CD practices, and GenAI API integrations with cost optimization * Implement monitoring, logging, alerting, and dashboards for model performance, data quality, and system health * Communicate technical concepts effectively to both technical and non-technical audiences through presentations, reports, and executive summaries * Apply responsible AI practices including fairness evaluation, bias detection, and model interpretability * Support governance documentation including system security plans, privacy impact assessments, and authority to operate processes * Contribute to building an AI/ML practice through documentation, capability development, and mentoring team members ## Related Videos - [How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge](https://www.wearedevelopers.com/videos/1328-how-to-avoid-llm-pitfalls-mete-atamel-and-guillaume-laforge) - [Collaboration Quantified: Lessons from Open Source Developer Networks](https://www.wearedevelopers.com/videos/1422-collaboration-quantified-lessons-from-open-source-developer-networks) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More](https://www.wearedevelopers.com/videos/869-inside-the-ai-revolution-how-microsoft-is-empowering-the-world-to-achieve-more) - [Integrate your Cognitive Assistant with 3rd-party DBs and software](https://www.wearedevelopers.com/videos/249-integrate-your-cognitive-assistant-with-3rd-party-dbs-and-software) - [Streaming AI Responses in Real-Time with SSE in Next.js & NestJS](https://www.wearedevelopers.com/videos/1630-streaming-ai-responses-in-real-time-with-sse-in-next-js-nestjs) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? 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