Intuitive Hiring: Data Scientist ($127K–$215K) in Blacksburg

Intuitive is seeking a Data Scientist to join its growing analytics and machine learning team in Blacksburg, Virginia. This role focuses on leveraging advanced statistical modeling, data engineering, and machine learning techniques to drive insights across healthcare technologies. The position offers a competitive salary range of $127K–$215K, reflecting both technical depth and strategic impact within a company known for innovation in robotic-assisted systems and data-driven healthcare solutions.

Job Overview

Job Description

The Operations Data Scientist plays a critical role in transforming how manufacturing teams see and understand their operations by building and operating data pipelines, models, and visualizations that deliver real‑time line visibility to manufacturing performance and associated key performance indicators (KPIs).  This role partners with Manufacturing Engineering, Automation Equipment and Test (AET) Engineering, Operations, Industrial Engineering, Quality, and IT/Data teams to architect reliable data flows from MES/ERP and equipment sources, transform raw signals into trusted semantic models, and surface insights via dashboards and alerts that drive business efficiencies and support continuous improvement (throughput, yield, cost, rework, OEE).

The ideal candidate thrives at the intersection of data engineering and operations.  They enjoy understanding how complex manufacturing systems work, uncovering hidden patterns in data, and turning raw information into intuitive analytics that drive action on the floor.  This role is perfect for someone who is energized by solving meaningful problems, partnering closely with cross‑functional teams, and owning the full lifecycle of data—from source to insight.

Essential Job Duties

• Develop, maintain, and enhance data pipelines that power manufacturing operations with high reliability and performance, balancing latency, reliability, and cost
• Build new integrations to close data gaps, ensuring end‑to‑end visibility across production lines, equipment, and MES/ERP systems
• Build dynamic, user‑friendly dashboards that provide clear, actionable insights for both leadership and shop‑floor teams
• Ensure data quality and KPI accuracy by identifying and resolving discrepancies between source systems and analytics outputs
• Implement proactive monitoring, data validation, and automated quality checks to deliver trusted, high‑availability datasets
• Serve as the analytics point of contact for Operations and Manufacturing Engineering – prioritize requirements, publish release notes, and host enablement sessions with line leaders and supervisors
• Work with data teams across the organization to ensure the right data is available to answer questions and monitor operations
• Communicate technical findings in a clear, compelling way that resonates with both technical and non‑technical audiences

Required Skills and Experience

• Minimum 2 years of experience in a professional role involving data (e.g. data engineering, data science, data visualizations)
• Minimum 1 year of programming or scripting experience (e.g. Python, C++, Java, Bash, PowerShell)
• Minimum 1 year of hands‑on experience using SQL
• Excellent communication (written and verbal), presentation and documentation skills
• Strong organization and time‑management skills, with the ability to manage multiple priorities in a dynamic environment
• Ability to distill complex information into clear insights that support operational improvements

Required Education and Training

• Bachelor’s degree in Business, Economics, Statistics, Engineering, Physics, or other quantitative field

Working Conditions

• None

Preferred Skills and Experience

• Minimum 2 years of hands-on experience building, operating, or supporting Operations data pipelines or analytics systems
• Experience with Snowflake SQL
• Experience in a manufacturing environment with understanding of MRP systems and factory workflows
• Proficiency with visualization and analytics tools such as Tableau, Smartsheet, or Posit
• Familiarity with statistical process control (SPC)

Selection Process

The hiring process is structured to evaluate both technical proficiency and problem-solving capabilities:

1. Application Screening
   Initial resume review focusing on relevant experience in data science, ML models, and domain exposure.
2. Technical Assessment
   May include coding challenges (Python/SQL), case studies, or ML problem-solving tasks.
3. Technical Interviews
   Multiple rounds covering:
   • Statistical analysis and modeling
   • Machine learning algorithms
   • Data handling and preprocessing
   • Real-world problem scenarios
4. Behavioral Interview
   Evaluation of communication skills, teamwork, and alignment with company culture.
5. Final Round / Hiring Manager Discussion
   Deep dive into past projects, impact, and role expectations.

How To Apply

1. Visit Intuitive’s official careers page.
2. Search for “Data Scientist – Blacksburg.”
3. Review the job description carefully to align your resume.
4. Submit your application with:
   • Updated resume
   • Cover letter (optional but recommended for differentiation)
5. Monitor your email for assessment or interview communication.