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Freelance Audio Machine Learning Jobs in Kansas (NOW HIRING)

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Freelance Audio Machine Learning information

What is the difference between Freelance Audio Machine Learning vs Freelance Audio Signal Processing?

AspectFreelance Audio Machine LearningFreelance Audio Signal Processing
Required SkillsMachine learning, programming, audio analysisDigital signal processing, audio engineering, software tools
Work EnvironmentData analysis, model development, algorithm designAudio editing, filtering, signal enhancement
Common EmployersTech companies, startups, research labsAudio production houses, broadcasting, music industry
CertificationsMachine learning, data science, programming certificationsAudio engineering, DSP certifications

Freelance Audio Machine Learning focuses on developing algorithms and models to analyze and interpret audio data using machine learning techniques. In contrast, Freelance Audio Signal Processing involves applying traditional digital signal processing methods to enhance or modify audio signals. Both roles require technical expertise but differ in their core methods and applications.

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Data Scientist 2

Data Scientist 2

Garmin International, Inc.

Olathe, KS • On-site

Full-time

Posted 7 days ago

Garmin rating

8.8

Company rating: 8.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

14th of 155 rated electronics manufacturers

Job description

Overview
We are seeking a full-time Data Scientist 2 at Garmin's U.S. headquarters in the Greater Kansas City 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)

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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