Data Scientist, Advanced Market Analytics & Modeling

Job Description

The Data Scientist, Advanced Market Analytics & Modeling will reside within the Global Market Analytics & Center of Excellence function, part of the overall Global Competitive, Market Intelligence & Analytics (MCI&A) team.

The candidate will be an expert in advanced market analytics and modeling, designing and executing sophisticated analytics using key market drivers as inputs into critical market sizing and models that support business planning, strategy, innovation, and KPI measurement of Olympus business and financial performance against market growth and competition.

This role will lead the development of driver-based market models, forecasting, and segmentation using scalable data science and AI techniques within a centralized workstream. The approach will efficiently integrate drivers such as procedure volumes, epidemiology, macroeconomics, market data, reimbursement trends, product launches, and business assumptions. The candidate will create scalable analytics across business units, fully leveraging both external and internal data assets for integrated, driver-based market models and quarterly market KPI analysis.

The candidate will collaborate with stakeholders both within MCI&A and cross-functionally to define and translate business needs into analytical terms, develop and implement advanced analytical solutions, establish standardized analytics processes, and provide data analytics and actionable insights to business support.

Job Duties

• Serve as a technical analytics expert: Translate complex business questions into actionable data queries and advanced analytical solutions that directly support business planning, strategy, innovation, and KPI measurement.
• Lead development of driver-based market models: Design, build, and validate sophisticated market models, forecasting, and segmentation using scalable data science and AI techniques, integrating key market drivers such as procedure volumes, epidemiology, macroeconomics, market data, reimbursement trends, product launches, and business assumptions.
• Execute advanced analytics initiatives: Develop and implement analytics that support critical business products, including global market models, procedure volume analytics, epidemiology analytics, and market KPI dashboards, ensuring accuracy, reliability, and business impact.
• Create scalable analytics solutions: Leverage both external and internal data assets to deliver integrated, driver-based market models and quarterly market KPI analysis across business units.
• Conduct deep-dive analyses: Apply statistical methods and machine learning (supervised and unsupervised) to uncover actionable insights, recommend strategies for continuous improvement, and support data-driven decision-making.
• Collaborate cross-functionally: Work closely with stakeholders within Market Intelligence & Analytics and across functions to define business needs, standardize analytics processes, and deliver insights that drive strategic objectives.
• Establish and maintain analytics standards: Develop and implement standardized analytics processes to ensure consistency, quality, and scalability of analytical solutions.
• Provide expert consultation: Advise stakeholders on market analytics methodologies, best practices, and emerging trends, supporting the organization’s continuous learning and proactive problem-solving culture.
• Deliver high-quality results: Demonstrate commitment to excellence, adaptability, and proactive problem-solving in a dynamic, fast-paced environment.

Job Qualifications

Required:

• Bachelor’s degree in data science, computer science, analytics, mathematics, engineering, or related disciplines. Advanced degree a plus.
• Minimum of 7 years of experience in data analysis, data science, or equivalent area; preferably in the healthcare, medical device, or life sciences.
• Minimum of 7 years of experience designing, implementing, and interpreting statistical analysis projects including forecasting, segmentation, and multivariate forecasting techniques.
• Minimum of 5 years project management experience in leading data projects cross-functionally.
• Experience with Python or R and expertise with enterprise data science platforms.
• Experience with AI model planning, implementation, and validation in enterprise environment.
• Advanced Excel skills.
• Ability to understand technical and clinical needs.
• Ability to transform business problems into data solutions.
• Strong analytical, conceptual, and problem-solving skills.
• Demonstrated experience for developing data capability for complex projects.
• Self-motivated, high commitment and dedication with proactive mind-set.
• Outstanding written and verbal communication (incl. PowerPoint, presentation skills).
• Detail oriented and high-quality deliverables.
• Project management skills and the ability to multitask with detailed follow-through on deadlines.
• Strong interpersonal and relationship building skills.
• Ability to successfully work with cross-functional teams.
• Travel <10% (domestic and international).