Garmin is looking to analyze complex data sets, develop machine learning models, and collaborate with cross-functional teams to provide actionable insights and AI solutions. The goal is to create health and fitness features that make complex data easy to understand and actionable for everyday users by analyzing biometric and activity data from Garmin devices to develop insights and predictive models that enhance user experience and motivate healthier lifestyles.
Requirements
- Experience using systems such as SQL, Python, or R
- Strong knowledge of machine learning frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch)
- Demonstrated understanding of advanced descriptive and inferential statistics
- Demonstrates expert knowledge in data analysis methods and tools
- Experience with structured database management systems
- Experience with applying statistical methods (e.g. time series analysis, NLP, deep learning, or reinforcement learning)
- Hands-on experience with MLOps, model deployment, and CI/CD for data science workflows
Responsibilities
- Under guidance or with minimal supervision, lead the collection, cleaning, and preprocessing of large datasets from diverse sources
- Conduct advanced exploratory data analysis (EDA) to identify trends, patterns, and anomalies that inform modeling efforts
- Design, implement, and refine predictive models using machine learning and statistical methodologies
- Collaborate with cross-functional teams to translate data-driven insights into product and strategy recommendations
- Design and deploy data pipelines for annotation, training and evaluation, and automate workflows to enhance efficiency
- Explore, evaluate, and experiment with emerging data science techniques, algorithms, and tools to improve model performance
- Support integration of models into production systems by coordinating with functional and technical teams and monitoring performance post-deployment
Other
- Bachelor's Degree in Engineering, Mathematics, Statistics, or another relevant technical field AND a minimum of 1 year of relevant experience OR an equivalent combination of education and relevant experience
- Excellent academics (cumulative GPA greater than or equal to 3.0 as a general rule)
- Demonstrated strong and effective verbal, written, and interpersonal communication skills
- Must be team-oriented, possess a positive attitude, and work well with others
- Driven problem solver with proven success in solving difficult problems
