Senior Data Scientist

Overview

The Senior Data Scientist is a senior technical leader responsible for executing and advancing the advanced analytics, machine learning, and AI strategy across the organization. This role focuses on applied data science at enterprise scale, including model development, experimentation, and operationalization. The role emphasizes deep Python-based modeling expertise, leadership of end-to-end ML lifecycle and MLOps, and delivery of scalable AI solutions (including large language models) that drive measurable business and mission outcomes for HUD programs (e.g., housing analytics, fraud detection, and intelligent document processing).

Responsibilities

• Execute and advance the enterprise data science and AI strategy aligned to organizational goals

• Serve as a trusted advisor on advanced analytics, machine learning, and AI adoption

• Lead high-impact AI/ML initiatives across business and technology teams

• Deliver time-boxed proofs of concept and MVP solutions that establish foundational AI capabilities and mature into production systems

• Translate complex business problems into analytical frameworks and scalable solutions

• Design, develop, and deploy advanced machine learning models, including predictive modeling and forecasting, NLP and large language models (LLMs), and recommendation systems and optimization models

• Apply advanced techniques such as deep learning, ensemble methods, and time series analysis

• Develop and scale modern AI solutions including Retrieval-Augmented Generation (RAG) and LLM-based workflows and applications

• Ensure models are robust, explainable, and production-ready

• Lead hands-on model development using Python as the primary programming language

• Build high-quality, reusable code for data processing and feature engineering, model development and evaluation, and experimentation and statistical analysis

• Establish best practices for Python-based data science development, including code quality, testing, and reproducibility

• Utilize core libraries such as Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow

• Partner with the Senior AI Engineer to operationalize end-to-end MLOps practices, including model versioning, tracking, and reproducibility, automated training and deployment pipelines, model monitoring, drift detection, and performance management

• Ensure continuous delivery and improvement of models in production

• Partner with engineering teams to productionize models while maintaining data science ownership of model integrity

• Establish standards for experimentation, A/B testing, and model validation

• Partner with data engineers and architects to build scalable data pipelines and platforms

• Define best practices for data preparation, feature engineering, and data quality

• Work with large-scale structured and unstructured datasets in cloud environments

• Ensure alignment between data science solutions and enterprise data architecture

• Establish best practices in model validation, explainability, and interpretability

• Ensure responsible AI practices including bias detection and mitigation

• Support model risk management and governance frameworks

• Promote transparency and auditability in AI/ML systems

• Communicate complex analytical insights to executive and non-technical stakeholders

• Influence decision-making through data storytelling and visualization

• Mentor and develop data scientists and analysts

• Lead cross-functional teams delivering high-impact data science solution

• Expert-level proficiency in Python for data science and machine learning (required)

• Deep expertise in machine learning, deep learning, and LLM-based approaches

• Experience with generative AI tooling, including RAG frameworks, embedding models, and vector databases

• Strong foundation in statistics, experimentation design, and model evaluation (including precision, recall, F1 score, and related performance metrics)

• Proven experience implementing MLOps frameworks and production ML systems (e.g., MLflow, Kubeflow, Azure ML, or SageMaker)

• Experience with big data tools (e.g., Spark) and cloud platforms (AWS, Azure, GCP

• Strong SQL skills for data extraction, transformation, and analysis

• Ability to translate ambiguous business questions into analytical solutions

• Strong communication and stakeholder engagement skills

• Proficiency with data visualization and BI tools (e.g., Power BI, Tableau)

• Familiarity with federal AI governance frameworks, including the NIST AI Risk Management Framework and OMB AI guidance

• Experience working with sensitive data, including PII safeguards such as anonymization, masking, and data loss prevention

Qualifications

•
US citizenship required

• Public Trust preferred

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or related field

• 10+ years of experience in data science, machine learning, or applied AI

• Demonstrated experience leading enterprise-scale data science initiatives

• Experience establishing data science or AI capabilities in organizations early in their AI maturity preferred

• Extensive hands-on Python experience delivering production-grade data science solutions

• Proven experience building and deploying ML models in production environments

• Strong experience with MLOps tools, pipelines, and lifecycle management

• Experience with LLMs, NLP, or generative AI applications

• Experience mentoring and leading data science teams

• Experience in AI governance, model risk management, or ethical AI

• Prior leadership role on federal programs (e.g., Lead Architect, Chief Engineer, Technical Director) preferred

• Experience with HUD or federal civilian agencies preferred

• Prior experience in consulting or client-facing environments preferred

Target Pay Range

The below listed pay range for this position is not a guarantee of compensation or salary. The final offered salary will be influenced by a host of factors including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications. Our employees value the flexibility at Pyramid Systems that allows them to balance quality work and their personal lives. We offer competitive compensation, benefits, to include our Employee Stock Ownership Program, FlexPTO, and learning and development opportunities.Pyramid Min

USD $145,560.00/Yr.Pyramid Max

USD $210,000.00/Yr.Why Pyramid?

Pyramid Systems, Inc. is an award-winning, technology leader, driving digital transformation across federal agencies. We empower forward-thinking innovations, accelerate production-ready software, and deliver secure solutions so federal agencies can meet their mission goals. Voted a Top Workplace, both regionally (Washington, DC) and Nationally (USA) the past 2 years (2023 and 2024) based on the feedback from our employees, we are headquartered in Fairfax, VA. and have a growing national footprint. We value and promote our Flexible Workplace approach because of the positive impacts it has on work-life integration. We remain committed to ensuring every employee’s voice is heard, performance and results are recognized and rewarded, development and advancement is a focus, and diversity, equity and inclusion is a company priority. We offer competitive compensation and benefits (including a recently launched Employee Stock Ownership Plan - ESOP), a robust performance-based rewards program, and we know how to have fun! Our people and culture have endured and delivered for our clients for nearly three decades.EEO Statement

Pyramid Systems, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.Originally posted on Himalayas