Advanced Analytics Consultant

Role Description

We are seeking a highly experienced and business-focused Advanced Analytical Consultant/Sr. Principal Data Scientist to join our Neuromodulation and Pelvic Health (NMPH) team. In this role, you will transform clinical and real-world data into strategic insights that influence clinical, regulatory, and market decisions.

This is a unique opportunity to build a patient-centered evidence analytics capability from the ground up, leveraging clinical and real-world data to inform critical clinical, regulatory, reimbursement, and business decisions. Working at the intersection of data science, healthcare innovation, and patient outcomes, you will help shape the future of Neuromodulation and Pelvic Health therapies through advanced analytics and real-world evidence while building a next-generation analytics function that drives meaningful patient impact and organizational success.

As a strategic partner and technical expert, you will work across therapies and functions to identify opportunities, develop advanced analytical solutions, and generate insights that improve patient outcomes and drive business success. You will help define a future-state analytics ecosystem by establishing scalable methodologies, tools, and data science capabilities that support evidence generation, innovation, and decision-making.

The ideal candidate combines deep technical expertise, healthcare innovation, and the ability to translate complex clinical data into actionable insights that influence decisions and create meaningful patient impact.

Key Responsibilities

• Data Science & Advanced Analytics
  • Analyze, clean, transform, and model complex clinical and real-world datasets to generate actionable insights.
  • Apply advanced statistical techniques to support forecasting, prediction, classification, and decision-making.
  • Analyze data from clinical studies, registries, claims databases, electronic health records (EHRs), publications, and other real-world data sources to identify trends, opportunities, and unmet needs.
  • Translate complex clinical, regulatory, and business questions into scalable analytical solutions.
  • Design, build, and maintain predictive models, analytics workflows, and decision-support tools that inform evidence generation and strategic planning.
• Artificial Intelligence & Machine Learning
  • Apply AI and machine learning approaches to accelerate data discovery, automate analyses, and improve analytical efficiency.
  • Develop, validate, and deploy predictive and prescriptive models using state-of-the-art methodologies.
  • Integrate scalable and repeatable data science solutions into enterprise platforms, workflows, and business processes.
  • Evaluate emerging AI and advanced analytics technologies to drive innovation and competitive advantage.
• Data Strategy, Management & Visualization
  • Ensure data quality, integrity, and governance across analytical projects and data assets.
  • Develop intuitive dashboards, reports, and visualizations that enable stakeholders to quickly understand and act on insights.
  • Extend internal datasets through integration of external data sources to enhance analytical capabilities and evidence generation efforts.
  • Conduct ad hoc analyses and effectively communicate findings and recommendations to technical and non-technical audiences.
• Cross-Functional Leadership & Partnership
  • Partner closely within Clinical Research and cross-functionally with Regulatory, Health Economics & Reimbursement, Marketing, R&D, and IT teams to address strategic business opportunities.
  • Identify, prioritize, and execute high-value analytics initiatives that advance organizational objectives.
  • Influence evidence generation strategies through analytical expertise and thought leadership.
  • Serve as a trusted advisor and subject matter expert on data science, AI, machine learning, and real-world evidence analytics.
  • Mentor and enable stakeholders on data-driven decision making and best practices in analytics.

Qualifications

• Bachelor's degree with a minimum of 10 years of experience in Data Analytics, Data Science, Business Analytics, Statistics, or a related quantitative field, OR Advanced degree (Master's or PhD) with a minimum of 8 years of experience in Data Analytics, Data Science, Business Analytics, Statistics, or a related quantitative field.

Nice to Have (Preferred Qualifications)

• Advanced degree (Master’s or PhD preferred) in Data Science, Statistics, Mathematics, Computer Science, Engineering, or another quantitative discipline.
• Experience working in regulated industries such as medical devices, healthcare, biotechnology, or pharmaceuticals is preferred.
• Strong understanding of clinical research, clinical trials, and real-world evidence (RWE) data.
• Significant experience translating complex data science analyses into actionable business and product strategies.
• Strong proficiency in Python and/or R for statistical analysis, machine learning, and predictive modeling.
• Demonstrated ability to incorporate AI-driven tools and automation into day-to-day analytical workflows.
• Proven track record developing, validating, and presenting machine learning models for predictive and prescriptive analytics to technical and non-technical stakeholders.
• Expertise in data visualization and communicating insights through clear, compelling dashboards and presentations.
• Deep understanding of machine learning, statistical inference, and their application to product development and decision-making.
• Excellent analytical, problem-solving, communication, and presentation skills, with the ability to influence cross-functional teams.
• Familiarity with synthetic data generation, simulation modeling, or digital twin technologies is a plus.

Location

Remote within US. This position is eligible to work remotely within the USA and requires <10% to support collaboration, business meetings, and the successful execution of projects and strategic initiatives.

Benefits

• Competitive Salary and flexible Benefits Package.
• Health, Dental and vision insurance.
• Health Savings Account.
• Healthcare Flexible Spending Account.
• Life insurance, Long-term disability leave.
• Dependent daycare spending account.
• Tuition assistance/reimbursement.
• Incentive plans, 401(k) plan plus employer contribution and match.
• Short-term disability.
• Paid time off.
• Paid holidays.
• Employee Stock Purchase Plan.
• Employee Assistance Program.
• Non-qualified Retirement Plan Supplement (subject to IRS earning minimums).
• Capital Accumulation Plan (available to Vice Presidents and above, or subject to IRS earning minimums).