AI/ML & Data Scientist SME

Zachary Piper Solutions is seeking an AI/ML & Data Scientist SME to support hybrid operations in Washington, DC. This role will analyze data, build clear visualizations, and automate cloud‑based workflows to deliver actionable insights.

Responsibilities for the AI/ML & Data Scientist SME include: • Analyze complex datasets and deliver actionable insights using BI, AI/ML, and predictive analytics. • Create clear, impactful Tableau/Power BI dashboards and communicate findings effectively. • Perform SQL-based ETL, manage relational databases, and ensure data quality through governance best practices. • Use AWS and Power Automate to modernize data workflows and automate scalable processes.

Qualifications for the AI/ML & Data Scientist SME include: • Bachelor’s degree (Master’s preferred) and 6+ years in AI/ML, data analysis, and visualization • Proficient in Python, SQL, and automated data workflows/pipelines • Strong Tableau/Power BI dashboard and reporting expertise • Familiar with AWS cloud services and Collibra Data Governance • Active DHS or Top Secret clearance

Compensation for the AI/ML & Data Scientist SME include: • Salary Range: $120,000 - $140,000 based on years of experience • Benefits: Medical, Dental, Vision, 401k Plan, PTO (Paid Time Off), Holidays, Sick leave as required by law

This job opens for applications on 1/20/2025. Applications for this job will be accepted for at least 30 days from the posting date

Keywords: AI/ML, data analytics, data visualization, Power BI, Tableau, SQL, ETL, Python, AWS, S3, EC2, RDS, Lambda, automation, Power Automate, data governance, Collibra, dashboards, reporting, predictive analytics, generative AI, data modeling, business intelligence, cloud computing, data pipelines, workflow automation, Oracle, PostgreSQL, MySQL, data quality, data integrity, data lineage, stakeholder engagement, insights, analytics solutions, data storytelling, relational databases, cloud modernization, analytics engineering, data processing, data extraction, KPI reporting, communication skills, cross-functional collaboration, technical analysis, data-driven decision-making, performance metrics, analytics strategy, enterprise data, trends and patterns

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