Operations Data Scientist

Company Description

It started with a simple idea: what if surgery could be less invasive and recovery less painful? Nearly 30 years later, that question still fuels everything we do at Intuitive. As a global leader in robotic-assisted surgery and minimally invasive care, our technologies—like the da Vinci surgical system and Ion—have transformed how care is delivered for millions of patients worldwide.

We’re a team of engineers, clinicians, and innovators united by one purpose: to make surgery smarter, safer, and more human. Every day, our work helps care teams perform with greater precision and patients recover faster, improving outcomes around the world.

The problems we solve demand creativity, rigor, and collaboration. The work is challenging, but deeply meaningful—because every improvement we make has the potential to change a life.

If you’re ready to contribute to something bigger than yourself and help transform the future of healthcare, you’ll find your purpose here.

Job Description

Primary Function of Position

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

Qualifications

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 environm