Planning Analyst

Job description

We are looking for a Planning Analyst to support data science and analytics initiatives across Global Operations. Minimizing supply chain risk and optimizing manufacturing operations are critical to enabling surgeons and healthcare institutions to deliver better patient outcomes. This is an entry-level role for a recent graduate beginning a data science career. The Data Scientist applies foundational data science and analytical concepts under general supervision, building toward greater independence over time.

This role is expected to bring curiosity and hands-on comfort with Gen AI and LLM tools, using them both to accelerate day-to-day analysis and to help prototype new AI-powered data products. Essential Job Duties (Specific responsibilities and tasks an individual would be expected to perform in the role. Additional job duties may be determined by functional people manager)

• Support data science and analytics initiatives across Global Operations under the guidance of senior team members
• Help translate well-defined business questions into analytical approaches with support from senior

Data Scientists

• Apply statistical methods and machine learning techniques to company data to generate insights
• Build and maintain reports, dashboards, and data products using the R and/or Python ecosystem
• Work with Snowflake and SQL to source, transform, and analyze datasets
• Use Gen AI and LLM-based coding tools (e.g., Claude Code) to accelerate the development, testing, and documentation of analytics solutions
• Explore and help prototype Gen AI / LLM-powered features and products that create new business value
• Present findings and recommendations to team members and business stakeholders
• Learn and apply best practices for reproducible, well-documented analytics
• Collaborate with data analysts and business users across Global Operations to support long-term reporting needs
• Continuously build technical skills, including in emerging Gen AI tooling, through mentorship and self-directed learning

Qualifications

Required Skills and Experience (Specific skills, knowledge, and experience that an individual must possess in order to successfully perform in job)

• Experience in either the Python or R ecosystem developing data-based solutions (through coursework, internships, or personal projects)
• Foundational knowledge of statistical techniques and machine learning concepts
• Familiarity with SQL, including querying across multiple tables
• Hands-on curiosity with Gen AI / LLM tools (e.g., Claude, Claude Code, or similar) for coding, analysis, and exploration
• Experience building dashboards, reports, or other data products (academic, internship, or professional)
• Proven problem-solving, quantitative, and analytical abilities
• Statistical skills and familiarity with common methods
• Excellent communication skills and the ability to present findings clearly
• Inquisitiveness with a desire for continuous learning and improvement Required Education and Training (As applicable
• Specific education and training that an individual must possess in order to successfully perform in job) Minimum Quantitative Bachelor’s degree (Statistics, Computer Science, Math, Data Science or Similar) or equivalent professional experience Typically 0-2 years of related experience with a University degree, or equivalent internship, research, or academic project experience Working Conditions (As applicable
• Any physical requirements for the job. If not applicable, state “none”) None Preferred Skills and Experience (As applicable
• Specific skills, knowledge, and experience that are not required to perform the job, but are desirable to have)
• Quantitative Advanced degree (Statistics, Computer Science, Math, Data Science or Similar)
• Experience with Git-based workflows and collaborative development
• Experience with CI/CD concepts
• Experience building or prototyping applications powered by LLMs (e.g., agentic workflows, RAG, chatbots)
• Experience with Posit platforms (Workbench, Connect)
• Internship, coursework, or project experience in manufacturing, supply chain, or operations