Data Scientist II

bostonscientific•Quincy, MA

18d•$72,800 - $138,300•Hybrid

About The Position

At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing – whatever your ambitions. About the role: As a Data Scientist II, you’ll support Boston Scientific’s growing data-driven initiatives by translating business requirements into actionable data solutions. You’ll work closely with cross-functional partners to develop, implement, and monitor predictive models and analytics tools that directly influence strategic decision-making. This role is ideal for someone with strong analytical acumen, technical curiosity, and a passion for leveraging data to create impact. Work model, sponsorship, relocation: At Boston Scientific, we value collaboration and synergy. This role follows a hybrid work model requiring employees to be in our local 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. Relocation assistance is not available for this position at this time.

Requirements

Bachelor's degree in data analytics, data science, or data engineering, or a related field
Minimum of 2 years' experience in a data analytics, data science, or data engineering.
Strong knowledge of data modeling, predictive analytics, and statistical analysis.
Proficiency in tools such as Python, R, SQL, or similar platforms.
Ability to communicate complex data concepts clearly to business stakeholders.

Nice To Haves

Experience building data pipelines and analytics infrastructure.
Familiarity with cloud-based platforms (e.g., AWS, Azure, or GCP).
Exposure to customer experience, marketing analytics, or operations analytics.

Responsibilities

Interact with business stakeholders to understand data requirements and translate them into data structures and modeling needs.
Assess the effectiveness and accuracy of new data sources and data gathering techniques.
Develop custom data models and algorithms to apply to datasets.
Use predictive modeling to optimize customer experience, revenue, ad targeting, and other business outcomes.
Define criteria for monitoring data model integrity during projects.
Drive data modeling and testing activities across projects.
Conduct quality assurance of analytics tools and methodologies.
Collaborate with functional teams to implement models and monitor outcomes.
Develop best practices for analytics including models, standards, and tools.
Build analytics tools that utilize data pipelines to deliver actionable business insights.
Create tools that support analytics and data science teams in optimizing solutions.
Partner with data and analytics experts to continuously improve data systems.
Demonstrate a commitment to patient safety and product quality by maintaining compliance with the Quality Policy and documented procedures.