Sr. Data Scientist/Machine Learning SME, DHS Public Trust - Washington, United States - FWDthink LLC

FWDthink LLC Washington, United States

3 weeks ago

Description

Job Description

Senior Data Scientist / Machine Learning Subject Matter Expert (SME) with DHS Public Trust Clearance - Remote

About FWDthink:

FWDthink is a consulting company specializing in technology solutions, education and government contracting. Founded in 2010, we support Federal, State, Local Government & Commercial clients, providing solutions in Technology, Acquisition Support, Financial Management, Education and Consulting.

At FWDThink, we use authenticity, simplicity & kindness to enable talent & service. Our model focuses on moving the mission forward and encourages experimentation, expression the disruption of paradigms that no longer serve the greater good. We are creative, nurturing and innovative. We are a company of creators with evolving interests. We think forward by aligning our resources, tools, and strategies to focus on the solution. Join us as we encourage and empower our employees

Job Summary:

Our team is seeking a Senior Data Scientist / Machine Learning Expert with specialized experience in Generative AI and Large Language Models (LLMs), chatbots, and natural language processing to contribute to transformative projects for a government client within the Department of Homeland Security (DHS).
The ideal candidate will possess a strong background in data science, machine learning, and the ability to leverage Azure's managed services and large language models (LLMs) to deliver innovative solutions

Key Responsibilities:

LLM and Chatbot Development

Lead the design and development of LLMs and chatbots, integrating them with cloud technologies for document processing applications.
Explore the capabilities of Azure's LLM offerings, such as Azure OpenAI Service, to enhance data analysis, natural language processing, and knowledge extraction.
Integrate LLMs into data science workflows to generate insights, summarize findings, and automate repetitive tasks.
Implement and manage machine learning models, including fine-tuning, version control, and continuous evaluation to improve performance.

Data Analysis and Machine Learning

Analyze and interpret complex datasets using advanced statistical techniques and machine learning algorithms.
Design, develop, and deploy machine learning models using Azure Machine Learning and other Azure services.
Preprocess and prepare data for model training, feature engineering, and model optimization.
Conduct data mining and preprocessing to prepare large datasets for training LLMs, ensuring data quality and relevance.

RAG Approach and Azure Services Integration

Understanding of the RAG approach, which combines retrieval of relevant information from a knowledge base with generation of responses using large language models.
Design and implement RAG-based solutions to enhance data analysis, question answering, and other data-driven applications.
Demonstrate proficiency in working with Azure's data and AI services, including Azure Cosmos DB, Azure Synapse Analytics, and Azure Databricks.
Leverage Azure's scalable and secure infrastructure to build and deploy data-driven applications.

Collaboration and Communication

Collaborate with cross-functional teams, including data engineers, software developers, and business stakeholders, to identify use cases and implement LLM-powered solutions.
Communicate complex model behaviors and results to non-technical stakeholders, translating data-driven insights into actionable recommendations.
Engage in knowledge transfer, providing training and support to team members and stakeholders on AI-driven features and capabilities.

Model Evaluation and Refinement

Analyze system outputs and user interactions to refine models and improve accuracy, fluency, and compliance with government standards.
Develop metrics to evaluate model performance and user satisfaction, using these insights to guide iterative model improvements.
Leverage Azure's managed services, such as Azure Cognitive Services and Azure Databricks, to accelerate model development and deployment.
Analyze system outputs and user interactions to refine models and improve accuracy, fluency, and compliance with government standards.

Required Qualifications:

Master's or Ph.D. in Computer Science, Artificial Intelligence, Statistics, or a related field.
At least 8 years of experience in data science or machine learning, with a proven track record in building and deploying LLMs and chatbot systems.
Strong programming skills in Python, including familiarity with AI and ML libraries (e.g., TensorFlow, PyTorch, NLTK, SpaCy, and LangChain).
Demonstrated experience with natural language processing, text embeddings, and generative AI models.
Familiarity with Azure services related to AI and ML, such as Azure Machine Learning, Azure Cognitive Services, and Azure Databricks.
Proficient in data manipulation and analysis with expertise in using data science toolkits and platforms.
Familiarity with version control systems, model deployment strategies, and MLOps practices.
Excellent problem-solving abilities, analytical skills, and attention to detail.
Strong written and verbal communication skills, with experience in explaining complex models to diverse audiences.

Preferred Qualifications:

Publications in relevant AI/ML journals or conferences.
Experience working on government projects, especially those involving secure and compliant data handling.
Certifications related to Azure AI Engineer, Data Scientist, or similar credentials.
If you possess the required skills and experience, and are excited to leverage Azure's managed services and LLMs to drive data-driven innovation, we encourage you to apply for this Data Scientist position. We offer a competitive salary, a dynamic work environment, and opportunities for growth and advancement.

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