Data Scientist 2
Boulder, Colorado
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- Work setup
- Unconfirmed
- Employment
- Unconfirmed
Tools in this posting
- Python
- R
- SQL
- NoSQL
- Spark
- Dask
- Matplotlib
- PyTorch
- TensorFlow
- scikit-learn
Source — Tool mentions in context
Essential Functions 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 Assist in developing and maintaining processes and tools to ensure model performance, reliability, and data quality Create and present compelling data visualizations and reports using advanced graphics and visualization tools Identify and leverage both internal and external datasets to drive innovation and support business solutions Contribute to the development of custom machine learning models and algorithms across diverse datasets Apply predictive modeling to improve user experiences, support revenue growth, and enable data-driven insights Support the definition of project scope and business expectations based on data-driven insights Provide mentorship and share best practices with junior team members under the guidance of senior staff Participate in peer reviews and contribute to the continuous improvement of team processes Demonstrate a commitment to ongoing learning of new technologies, frameworks, and methodologies Ensure data quality, adherence to governance standards, and compliance with data privacy and AI-related regulations Basic Qualifications Bachelor's Degree in Computer Science, Electrical Engineering, Computer Engineering, Software Engineering, Aerospace Engineering, Math or Physics or a technical field (such as CIS or IT) relevant to the essential functions of this job description AND a minimum of 1 year of relevant experience 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 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 Consistently demonstrates quality and effectiveness in work documentation and organization Desired Qualifications 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 Exposure to distributed computing (e.g., Spark, Dask) and NoSQL databases Understanding of A/B testing and causal inference Experience working with unstructured data (text, images, audio, etc.) Familiarity with data visualization tools (i.e. Matplotlib, Seaborn) The deadline to apply to this role is Sunday, October 4, 2026.
Job description
Overview We are seeking a full-time Data Scientist 2 at Garmin's location in the Boulder/Louisville area. In this role, you will be responsible for analyzing complex data sets, developing machine learning models, and collaborating with cross-functional teams to provide actionable insights and AI solutions. In addition, under guidance or with minimal supervision, this role will apply machine learning, statistical analysis, and data engineering techniques to address challenging business problems. Essential Functions 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 Assist in developing and maintaining processes and tools to ensure model performance, reliability, and data quality Create and present compelling data visualizations and reports using advanced graphics and visualization tools Identify and leverage both internal and external datasets to drive innovation and support business solutions Contribute to the development of custom machine learning models and algorithms across diverse datasets Apply predictive modeling to improve user experiences, support revenue growth, and enable data-driven insights Support the definition of project scope and business expectations based on data-driven insights Provide mentorship and share best practices with junior team members under the guidance of senior staff Participate in peer reviews and contribute to the continuous improvement of team processes Demonstrate a commitment to ongoing learning of new technologies, frameworks, and methodologies Ensure data quality, adherence to governance standards, and compliance with data privacy and AI-related regulations Basic Qualifications Bachelor's Degree in Computer Science, Electrical Engineering, Computer Engineering, Software Engineering, Aerospace Engineering, Math or Physics or a technical field (such as CIS or IT) relevant to the essential functions of this job description AND a minimum of 1 year of relevant experience 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 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 Consistently demonstrates quality and effectiveness in work documentation and organization Desired Qualifications 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 Exposure to distributed computing (e.g., Spark, Dask) and NoSQL databases Understanding of A/B testing and causal inference Experience working with unstructured data (text, images, audio, etc.) Familiarity with data visualization tools (i.e. Matplotlib, Seaborn) The deadline to apply to this role is Sunday, October 4, 2026. Garmin International is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, citizenship, sex, sexual orientation, gender identity, veteran's status, age or disability. This position is eligible for Garmin's benefit program. Details can be found here: Garmin Benefits
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Boulder, Colorado
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- First seen by us
- Oct 1, 2026
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- Last seen by us
- Oct 2, 2026
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