Garmin Cluj
Garmin Cluj
Garmin Cluj navigatsiya, fitnes, salomatlik va kundalik hayotdagi ulangan tajribalar uchun texnologiyalarni ishlab chiqishga yo‘naltirilgan Garmin kompaniyasining mintaqaviy ofisidir. Uning faoliyati GPS navigatsiya tizimlari, aqlli soatlar va fitnes kuzatuv qurilmalari kabi mahsulotlarga hissa qo‘shib, ochiq havoda sayohat qilishdan tortib salomatlikni kuzatish va avtomobilda safar qilishgacha bo‘lgan faoliyatlarni qo‘llab-quvvatlaydi. Jamoa butun dunyodagi foydalanuvchilar uchun mo‘ljallangan ishonchli yechimlarni yaratadi.

Data Scientist – Machine Learning, Hybrid Romania

Join Garmin Cluj’s data and AI team to build, deploy, and monitor machine-learning solutions for outdoor technology products.

Tavsif

  • Partner with engineering, product, and business stakeholders to establish requirements and deliver data-driven solutions
  • Analyze large, complex datasets to identify meaningful trends, patterns, and actionable insights
  • Evaluate machine-learning and AI approaches for practical product applications
  • Build scalable pipelines and workflows across the full data-science lifecycle
  • Establish evaluation frameworks and metrics for assessing model and product performance
  • Present complex analytical findings clearly to non-technical audiences using visualizations and presentations
  • Maintain deployed models for reliability, scalability, and performance while monitoring results and refining them over time
  • Drive the creation of custom machine-learning models and algorithms aligned with business needs

Talablar

  • Bachelor’s degree in computer science, electrical engineering, computer engineering, software engineering, mathematics, physics, or a related technical field, plus at least five years of relevant experience; equivalent education and experience may also qualify
  • Strong programming ability in Python and/or Java
  • Experience querying and working with database systems, including SQL
  • Advanced knowledge of machine-learning system design and modern AI methods such as LLMs, RAG, and MCP
  • Expertise in descriptive and inferential statistics, including applying them to large, imperfect datasets and real-world challenges
  • Expert-level knowledge of data-analysis methods and tools
  • Strong verbal, written, and interpersonal communication skills
  • Collaborative, team-oriented approach and a constructive attitude
  • Demonstrated ability to solve complex problems effectively
  • Consistent attention to the quality, clarity, and organization of work documentation
  • Preferred: experience with time-series analysis, NLP, deep learning, or reinforcement learning
  • Preferred: familiarity with MLOps, including experiment tracking, model deployment, and CI/CD for data-science workflows
  • Preferred: advanced knowledge of A/B testing and causal inference
  • Preferred: experience analyzing unstructured text, image, or audio data
  • Preferred: advanced use of visualization tools such as Matplotlib, Seaborn, or Tableau
  • Preferred: experience using AWS, Azure, or Google Cloud for data-science workflows
  • Preferred: experience with real-time data-processing platforms such as Kafka

Imtiyozlar

  • 24 days of annual leave, additional days based on tenure, and compensation for public holidays
  • Health-plan subscription and an annual allowance for glasses
  • Monthly allowance for sports and wellbeing activities
  • Access to local and global development programs covering training, mentoring, and technical and leadership growth
  • E-learning access and support for attending technical conferences
  • Company loyalty bonus and additional bonuses for holidays and personal events
  • Meal vouchers
  • Substantial discounts on Garmin products
  • Employee stock-purchase plan
  • Employer contribution to the Pillar III retirement plan
  • Opportunities to test and borrow Garmin products
  • Wellbeing, sports, and community events including classes, hackathons, sports activities, and parties
  • Additional benefits may be available during the recruitment process

O‘xshash ish o‘rinlari