Data Scientist job opportunity at Garmin Cluj.

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Date2025-11-17T14:33:32.537Z bot
Garmin Cluj Data Scientist
Experience: 5-years
Pattern: Full-time
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loacation Cluj-Napoca, Romania
loacation Cluj-Napoca....Romania

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. Bachelor's Degree in Computer Science, Electrical Engineering, Computer Engineering, Software Engineering, Math or Physics or a technical relevant to the essential functions of this job description AND a minimum of 5 years of relevant experience OR an equivalent combination of education and relevant experience. Extensive experience using systems such as SQL, Python, or R. Strong expertise in machine learning frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch). Demonstrated expertise in advanced descriptive and inferential statistics, including the ability to apply these techniques to complex data sets and real-world problems. Demonstrated 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. Would be a plus Advanced experience with structured database management systems and distributed computing. Expertise in time series analysis, NLP, deep learning, or reinforcement learning. Leadership in MLOps, model deployment, and CI/CD for data science workflows. Advanced understanding of A/B testing and causal inference. Experience working with unstructured data (text, images, audio, etc.). Advanced experience with data visualization tools (i.e. Matplotlib, Seaborn, Tableau). Experience working with cloud platforms (e.g. AWS, Azure, GCP) for data science workflows. Experience with real-time data processing technologies (e.g. Apache, Kafka).

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