Systems Architect - Data Science & Advanced Analytics

Analytica•Bethesda, MD

About The Position

Analytica is seeking a Systems Architect – Data Science & Advanced Analytics to provide strategic and technical leadership in designing, implementing, and modernizing enterprise data and advanced analytics solutions. This role serves as the lead architect for data science initiatives, responsible for developing scalable analytics environments, machine learning solutions, and enterprise data architectures with a strong emphasis on Databricks, Apache Spark, and modern cloud-based data platforms. The ideal candidate will work closely with data scientists, data engineers, business stakeholders, and technical leadership to develop innovative analytics solutions that transform complex data into actionable insights. This individual will provide technical vision, establish best practices, and lead the adoption of advanced analytics and machine learning capabilities across the organization.

Requirements

Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, Mathematics, or a related technical discipline (Master's preferred).
10+ years of progressive experience designing and implementing advanced analytics, machine learning, or Big Data solutions.
Demonstrated experience serving as a technical lead or subject matter expert for enterprise data science initiatives.
Experience leading technical teams and architecting large-scale analytics platforms.
Experience architecting enterprise-scale data science and advanced analytics platforms.
Experience developing AI/ML solutions supporting mission-critical or large-scale business operations.
Knowledge of modern data governance and responsible AI principles.
Experience with experimentation frameworks, model operationalization, and analytical product development.
Familiarity with Agile product development and collaborative data science workflows.
Machine Learning model development and lifecycle management
Statistical analysis and predictive modeling
Artificial Intelligence and Advanced Analytics methodologies
Feature engineering and model evaluation techniques
Data exploration and analytical solution design
Databricks Lakehouse Platform
Apache Spark
Delta Lake
Distributed data processing frameworks
ETL/ELT and modern data pipeline architectures
Data modeling and enterprise data architecture
Advanced analytics solution design
Business Intelligence and data visualization concepts
Dashboard and reporting architecture
Data storytelling and insight generation
Technical strategy development
Enterprise architecture governance
Cross-functional team leadership
Stakeholder engagement and executive communication
Mentoring and coaching technical teams

Nice To Haves

Master's degree

Responsibilities

Serve as the Lead Architect for enterprise Data Science and Advanced Analytics initiatives.
Develop and drive the organization's vision and strategy for Big Data, Artificial Intelligence, and Machine Learning solutions.
Lead the design and implementation of scalable data science environments that support experimentation, model development, validation, and deployment.
Provide technical leadership and mentorship to Data Scientists, Machine Learning Engineers, and Analytics teams.
Identify emerging technologies and analytical methodologies that improve organizational capabilities and mission outcomes.
Architect end-to-end machine learning and advanced analytics solutions using modern data platforms and distributed computing frameworks.
Design scalable workflows for data preparation, feature engineering, model training, evaluation, and production deployment.
Collaborate with cross-functional teams to translate business and mission objectives into advanced analytical solutions.
Guide the development of predictive models, statistical analyses, optimization models, and AI-driven decision support tools.
Establish best practices for model governance, reproducibility, documentation, and performance monitoring.
Design enterprise data architectures that enable large-scale analytics and machine learning workloads.
Lead the development of data pipelines and analytical frameworks utilizing Databricks Lakehouse architecture, Delta Lake, and Apache Spark.
Ensure data solutions are scalable, reliable, high-performing, and aligned with enterprise architecture standards.
Architect integrated data ecosystems that support structured, semi-structured, and unstructured data sources.
Lead modernization initiatives that enhance data accessibility, analytical capabilities, and operational efficiency.
Partner with executive leadership and business stakeholders to define data and analytics roadmaps.
Translate complex technical concepts into business-focused recommendations and strategic initiatives.
Lead architecture reviews and provide expert guidance on enterprise analytics solutions.
Foster collaboration between Data Science, Data Engineering, and business teams to deliver high-impact analytical products.