Systems Architect - Data Science & Advanced Analytics

Analytica

Bethesda (MD)

On-site

USD 165,000 - 210,000

Full time

14 days+

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Benefits offered by this job

Bonuses

Employer-paid health care

Training and development funds

401k match

Job summary

Analytica seeks a Systems Architect – Data Science & Advanced Analytics to lead enterprise data science initiatives, shaping scalable analytics environments and ML solutions with Databricks, Spark, and modern cloud platforms.

You will collaborate with data scientists, engineers, and leadership to translate business goals into advanced analytics, establish best practices, and drive adoption across the organization.

Qualifications

Bachelor’s degree or higher in a technical field; Master’s preferred.
10+ years of progressive experience in analytics, ML, or Big Data.
Experience as a technical lead for enterprise data science initiatives.
Experience architecting large-scale analytics platforms and teams.

Responsibilities

Lead Architecture for enterprise Data Science and Advanced Analytics initiatives.
Develop the vision and strategy for Big Data, AI, and ML solutions.
Design scalable data science environments for experimentation, model development, and deployment.
Mentor Data Scientists, ML Engineers, and Analytics teams.
Guide governance, reproducibility, and performance monitoring for models.

Skills

10+ years experience

Technical leadership

Enterprise data platforms

Architecture leadership

Agile methodologies

Cross-functional collaboration

Data governance knowledge

ML/AI solution design

Education

Bachelor’s degree in Computer Science, Data Science, Statistics, Engineering, Mathematics, or related field

Master’s degree preferred

Tools

Databricks Lakehouse

Apache Spark

Delta Lake

Job description

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.

Analytica has been recognized by Inc. Magazine as a fastest-growing private US small business. We work with U.S. government customers in health, civilian, and national security missions. Analytica offers competitive compensation with opportunities for bonuses, employer paid health care, training and development funds, and 401k match.

Key Responsibilities

Data Science Leadership

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.

Advanced Analytics & Machine Learning

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.

Data Architecture & Big Data Solutions

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.

Strategic Collaboration

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.

Required Qualifications

Experience

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.

Required Technical Skills

Data Science & Machine Learning