Lead Systems Architect, Data Science & AI Analytics

Analytica; Bethesda (MD); On-site; USD 165,000 - 210,000; Full time

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 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.