Sales Operations Data Scientist

Accountabilities

• • Define, develop, and maintain KPIs that measure product health, customer engagement, commercial performance, and marketplace dynamics.
  • Analyze customer behavior, product usage, and business trends to identify risks, opportunities, and drivers of future performance.
  • Translate complex analytical findings into clear, actionable recommendations for product, commercial, and leadership teams.
  • Partner cross-functionally with teams including sales, marketing, finance, HR, and product to identify business questions and deliver data-driven solutions.
  • Collect, clean, transform, and analyze large datasets from internal and external sources, ensuring the accuracy and integrity of analytical outputs.
  • Develop predictive models and statistical analyses that help explain business behavior and inform strategic decisions.
  • Build and automate recurring reports and analytical processes to improve efficiency, consistency, and timeliness.
  • Improve data accessibility and quality by supporting scalable data solutions, ETL processes, and data architecture.
  • Monitor and optimize data pipelines and data quality while identifying opportunities for continuous process improvement.
  • Implement and maintain appropriate data governance, security, and quality controls across data workflows.
  • Develop clear data visualizations and dashboards that make complex information accessible and actionable for diverse stakeholders.
  • Help foster a culture of data-driven decision-making and continuous improvement across the commercial organization.

  Requirements

  • Minimum of 8 years of experience as a Data Scientist, Data Analyst, or in a closely related analytics-focused role, with demonstrated impact on business strategy and decision-making.
  • Bachelor’s degree in Computer Science, Mathematics, Statistics, Engineering, or a related technical discipline; an advanced degree or relevant certification is a plus.
  • Strong proficiency in SQL and at least one high-level programming language such as Python, R, Scala, or Java.
  • Demonstrated expertise in statistical analysis, predictive modeling, data extraction, data cleaning, and data visualization.
  • Experience working with large datasets and translating analytical findings into practical business recommendations.
  • Strong understanding of product and customer analytics, with the ability to identify meaningful patterns, trends, risks, and opportunities.
  • Experience with ETL processes and data engineering concepts; exposure to Azure cloud services or Microsoft Fabric is a plus.
  • Experience with data visualization platforms such as Power BI is preferred.
  • Ability to work effectively with cross-functional stakeholders, particularly across sales, marketing, finance, HR, and product functions.
  • Strong communication skills, with the ability to explain complex technical and analytical concepts clearly and concisely to both technical and non-technical audiences.
  • High level of accountability, curiosity, adaptability, and commitment to continuous learning.
  • Comfortable working independently, taking ownership of projects, and delivering results in a fast-paced and evolving environment.
  • Experience in the medical device or healthcare industry is strongly preferred but not required.
  • A growth mindset and genuine interest in developing robust, scalable, and efficient data solutions.

  Benefits

  • 100% remote position within the United States, supporting US core business hours.
  • Comprehensive healthcare benefits effective from day one.
  • Medical, dental, and vision insurance.
  • Life insurance, FSA, HSA, short-term and long-term disability coverage.
  • Critical illness and accident insurance options.
  • Competitive base salary plus eligibility for a corporate bonus program.
  • Potential eligibility for equity.
  • Generous paid time off.
  • 16 paid holidays, including a company-wide summer recharge week in July.
  • 12 weeks of paid parental leave after 90 days of employment.
  • Monthly cell phone stipend.
  • Opportunity to join a growing team and build foundational analytics and data capabilities with meaningful business impact.