At Garmin we create products that are designed indoors for outdoor activities. We do this to enable our customers to make the most of their time spent pursuing their passions.
We are seeking a Data Scientist to provide technical leadership and strategic project planning for data science initiatives related to new products, applications, or systems within the company. This role involves leveraging advanced data science techniques to drive innovation and deliver actionable insights that support business objectives. The Data Scientist will collaborate with cross-functional teams, mentor junior data scientists, and ensure the successful implementation and integration of data-driven solutions.
Responsibilities
- Lead the design, development, and deployment of advanced machine learning models and algorithms to solve complex business problems.
- Provide technical leadership and mentorship to junior data scientists, fostering a culture of continuous learning and improvement.
- Drive the strategic planning and execution of data science projects, ensuring alignment with business goals and timelines.
- Collaborate with cross-functional teams, including engineering, product management and business stakeholders, to define project requirements and deliver data-driven solutions.
- Conduct advanced exploratory data analysis (EDA) to uncover insights, trends, and patterns in large and complex datasets.
- Develop and implement scalable data pipelines and workflows to support the end-to-end data science lifecycle.
- Evaluate and integrate new data science techniques, tools, and technologies to enhance the company’s data capabilities.
- Communicate complex analytical concepts and results to non-technical stakeholders through clear and compelling data visualizations and presentations.
- Ensure the robustness, scalability, and performance of deployed models, monitoring their impact and iterating as necessary.
- Champion best practices in data science, including data governance, model validation, and ethical AI considerations.
- Identify and prioritize opportunities for leveraging data to drive business growth and operational efficiency.
- Lead the development of custom machine learning models and algorithms tailored to specific business needs.
- Own team-level success by monitoring, modifying and creating team processes to help ensure consistency, continuity, efficiency and impact in analysis and ML pipelines.
- Pioneer peer reviews and foster a culture of continuous improvement and learning.
- Develop and enforce data governance policies and procedures to ensure data integrity and security.
- Monitor compliance with data privacy laws and regulations and implement measures to protect sensitive information.
