Senior Manager, Data Science & Advanced Analytics
About The Position
LivaNova is seeking a Senior Manager to lead the day-to-day delivery of high-impact data science and advanced analytics for business-unit and enterprise stakeholders. The team enables data-driven decisions and supports stakeholder automation and AI needs through dashboarding, statistical modeling, machine learning, forecasting, survival analysis, AI-enabled solutions, and self-service tools. This is a player-coach role. The Senior Manager will lead and develop applied data scientists and analysts, prioritize the team's portfolio, and partner with stakeholders to turn business questions into scalable analytical products and actionable recommendations. The role combines technical judgment and hands-on contributions with people leadership, stakeholder alignment, quality standards, and adoption. The position is US remote, with optional hybrid work in Houston, Arvada, or NYC. Limited travel, generally less than 10%, may be required.
Requirements
- Bachelor’s degree in data science, statistics, mathematics, computer science, engineering, economics, or a related quantitative field.
- At least 7 years of experience applying data science and advanced analytics to real-world business problems, including ownership from problem definition through adoption and measurement.
- At least 3 years of people leadership experience, including coaching technical team members, reviewing work, setting standards, and coordinating delivery across multiple projects.
- Expertise in Python or R and strong working knowledge of SQL.
- Experience with modern cloud analytics environments and version-controlled development workflows.
- Demonstrated knowledge of statistical modeling and machine-learning methods, with sound judgment about when simpler analytical approaches are more appropriate.
- Experience building trusted partnerships with commercial, marketing, sales, operations, finance, strategy, or other business functions.
- Ability to synthesize complex analyses into concise, decision-oriented recommendations for senior leaders and non-technical audiences.
- Experience developing self-service analytics, repeatable products, or transition plans that shift routine work closer to business users.
- Excellent prioritization, organizational, and change-management skills in a fast-paced, evolving environment.
- Working knowledge of responsible AI, data privacy, model governance, and validation practices.
Nice To Haves
- An advanced degree in a quantitative field.
- Experience in a regulated industry.
- Healthcare, medical-device, CRM, electronic health record, or claims-data experience.
- Interest in learning about other areas of the business, such as commercial, operations, finance, and clinical.
Responsibilities
- Lead, coach, and develop data scientists and analysts, setting expectations for technical quality, business impact, documentation, communication, and professional growth.
- Manage day-to-day portfolio delivery across commercial and enterprise stakeholders, balancing strategic initiatives, recurring commitments, and urgent needs.
- Partner with business leaders to identify opportunities for advanced analytics, machine learning, forecasting, causal inference, segmentation, optimization, automation, and AI-enabled decision support.
- Translate ambiguous business questions into scoped analytical products with defined users, success measures, timelines, risks, and adoption plans.
- Review analytical design and provide technical guidance on model selection, validation, interpretation, explainability, bias assessment, and communicating limitations.
- Transition basic reporting, routine data pulls, and repeatable analyses to governed self-service solutions or appropriate business owners, including enablement and handoffs.
- Develop reusable approaches, shared standards, and scalable workflows that reduce duplication and improve speed, consistency, and maintainability.
- Communicate insights as clear business stories, with recommendations, trade-offs, and next steps tailored to technical and executive audiences.
- Collaborate with IT, data, privacy, legal, compliance, and business teams on data access, platforms, deployment, governance, and responsible analytics and AI use.
- Oversee measurement of solution adoption, model performance, operational outcomes, and business value, using results to guide iteration and prioritization.
- Support talent planning, hiring, resource allocation, vendor or contractor coordination, and development of the team's operating model.
- Maintain technical depth to guide complex work, troubleshoot critical issues, and contribute directly to priority analyses when appropriate.
Benefits
- Health benefits, including medical, dental, and vision.
- Personal and vacation time.
- Retirement and Savings Plan (401K).
- Employee Stock Purchase Plan.
- Training and Education Assistance.
- Bonus Referral Program.
- Service Awards.
- Employee Recognition Program.
- Flexible Work Schedules.
- Discretionary annual bonus.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
