AI Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Conduct analysis, modeling, and simulation of data to support HUD AI/ML proofs of concept and pilot projects.

• Create, develop, and implement advanced analytics, machine learning models, predictive simulations, and AI-driven solutions.

• Build, train, validate, and deploy machine learning models, predictive analytics solutions, and statistical frameworks.

• Design and execute simulations, forecasting models, optimization techniques, and decision-support systems.

• Examine structured and unstructured datasets to uncover patterns, trends, risks, and opportunities.

• Carry out feature engineering, data preparation, cleansing, transformation, and quality assessments.

• Assess model performance and refine algorithms to enhance accuracy, reliability, and business impact.

• Assist with AI-enabled solutions utilizing machine learning, generative AI, LLMs, and emerging AI technologies.

• Collaborate with AI engineering teams to operationalize models and integrate them into enterprise applications and workflows.

• Develop methodologies for risk detection, anomaly identification, behavioral analysis, and decision intelligence.

• Engage in AI experimentation, proof-of-concept development, pilot initiatives, and production deployments.

• Architect the target-state Enterprise AI Security Platform, encompassing platform components, security services, data flows, APIs, integration patterns, trust boundaries, and deployment models.

• Partner with engineering teams to construct scalable data pipelines and analytics workflows.

• Work with SQL, NoSQL, cloud-native platforms, and distributed data environments.

• Contribute to MLOps, reproducible workflows, version-controlled development, and model lifecycle management.

• Support the integration of machine learning solutions with APIs, cloud services, data platforms, and business applications.

• Document models, assumptions, methodologies, testing procedures, and decision logic.

• Maintain reproducible and auditable workflows that support governance, compliance, and operational excellence.

• Ensure adherence to responsible AI principles, privacy requirements, cybersecurity standards, and ethical AI practices.

• Contribute to model governance, validation frameworks, and risk management activities.

• Collaborate with stakeholders, architects, engineers, UX teams, and business leaders to establish analytical requirements and success metrics.

• Present findings, recommendations, and technical concepts to both technical and non-technical audiences.

• Mentor junior team members and promote data science best practices and standards.

⛳️ Requirements

• Over 5 years of professional experience in data science, machine learning, advanced analytics, or applied AI.

• Proven experience in developing and deploying predictive models and machine learning solutions in production settings.

• Strong background in statistical analysis, machine learning algorithms, and data modeling techniques.

• Experience with large-scale datasets and modern data platforms.

• Proficient programming skills in Python and contemporary data science frameworks.

• Familiarity with collaborative Agile or product-focused development environments.

• Ability to successfully pass required background checks and obtain or maintain customer approvals or government clearance as needed.

• Must have legal authorization to work in the United States without sponsorship, both now and in the future.

• Preferred experience with enterprise-scale AI, cloud-based analytics platforms, or advanced AI/ML ecosystems.

• Familiarity with Generative AI, LLMs, RAG, vector databases, and AI agent frameworks is a plus.

• Experience in supporting federal government, regulated, or highly governed environments is preferred.

• Knowledge of AI governance, model risk management, privacy, security, and responsible AI frameworks is a plus.

• Experience with MLOps, CI/CD pipelines, and model monitoring is preferred.

• Proficient in Python with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, and/or PyTorch.

• Experience with SQL, NoSQL databases, Apache Spark, Kafka, cloud data platforms, and API integration.

• Knowledge in predictive modeling, statistical analysis, simulation and forecasting, ML lifecycle management, model evaluation and validation, as well as generative AI/LLM concepts.

• Experience with visualization tools like Plotly, Matplotlib, and Seaborn.

• Familiarity with Git/GitHub/GitLab, MLOps, CI/CD, reproducible workflows, and model governance.

• A Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field is required.

• A Master's degree and relevant professional certifications are preferred.

• Ability to sit for extended periods at a desk and work on a computer.

• May occasionally need to lift up to 25 pounds.

🏝️ Benefits

• Flexible remote work arrangement.

• 10–15% annual travel within the U.S. associated with the role.

• Opportunity to influence enterprise-scale AI initiatives.

• Chance to develop advanced decision-support solutions.

• Opportunity to contribute to the establishment of best practices for responsible AI, model governance, and data-driven innovation.