Manager of Data Science and Algorithms

Boston Scientific•Santa Clarita, CA

21d•$106,800 - $202,900•Hybrid

About The Position

Boston Scientific was recognized as a Glassdoor Best Place to Work in 2026, ranking No. 15 on the Top 100 list, reflecting the culture our employees experience every day. The Manager of Data Science and Algorithms leads a talented team of data scientists and engineers dedicated to building best-in-class data products that improve patient outcomes. In addition to leading the team, this individual collaborates cross-functionally with R&D, product marketing, software development, clinical research, IT, regulatory, health economics and reimbursement, and quality teams. The ideal candidate embraces innovation and a customer-centered mindset and is confident making data-driven decisions under uncertainty across multiple simultaneous product development initiatives. They serve as a subject matter expert for the team, championing new tools, methods, and technologies while fostering a culture of growth, development, and technical excellence. At Boston Scientific, we value collaboration and synergy. This role follows a hybrid work model requiring employees to be in our Valencia, CA office at least three days per week. Boston Scientific will not offer sponsorship or take over sponsorship of an employment visa for this position at this time.

Requirements

Master’s degree in Computer Science, Software, Biomedical or Neuro Engineering, Statistics, Biostatistics, or a related field.
Minimum of 7 years' experience building algorithms and/or data products from early concept through production.
Experience with neuromodulation systems.
Experience in clinical studies, including data collection design, analysis, and publication.
Experience defining data collection methodologies and analyzing data from digital applications and IoT devices.
Experience working with data from regulated medical products, including digital health and implantable devices.
Proven experience creating and implementing data governance models for health data that may include PII/PHI.
Experience in setting direction and goals for data scientists, analysts, and data engineers.
Demonstrated ability to define and prioritize needs for data products.
Experience managing external data-related collaborations and partnerships.
Experience with AWS cloud computing tools.
Ability to travel up to 25%.

Nice To Haves

PhD in Computer Science, Software, Biomedical or Neuro Engineering, Statistics, Biostatistics, or a related discipline.
Previous experience in a management or team leadership role.
Experience delivering scalable data products in a healthcare or regulated environment.
Background in clinical or scientific research.
Strong analytical skills and a demonstrated commitment to data-driven decision-making.
Hands-on coding experience with Python, R, or similar languages.
Track record of fostering collaborations between academia and industry, including publications and grant writing.
Strong public speaking skills with the ability to present to scientific and medical audiences.

Responsibilities

Develop and grow data science talent and technical expertise within the team.
Lead functional deliverables, ensuring technical excellence in product and algorithm development.
Provide direction, mentorship, and approval for technical strategies, roadmaps, and approaches.
Lead technical advancement initiatives and mature internal processes and procedures related to data science.
Champion ongoing intellectual property generation by both self and team members.
Motivate, mentor, and support staff in achieving career development goals.
Ensure effective staffing and support for data product and algorithm development from concept through production.
Collaborate with cross-functional teams to integrate data products and algorithms into the broader product portfolio.
Represent the team in presentations and technical reviews with clinicians and external stakeholders.
Manage team budget, resources, and schedules to meet department objectives.
Contribute to overall department strategy and planning.
Lead efforts to define and implement data governance models, especially for sensitive health data (PII/PHI).
Support external partnerships and collaborations involving data development and research.