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Data Scientist

LinkedIn Skechers Manhattan Beach, CA
Not Applicable Posted April 3, 2026 Job link
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Requirements
  • Proficiency with programming and data analysis using Python, Spark, and ML frameworks (NumPy, Pandas, Sci-kit Learn, XGBoost, TensorFlow, PyTorch).
  • Strong mathematical foundation in statistics, probability, optimization algorithms, linear algebra and AI technologies.
  • Working knowledge of statistical and machine learning techniques including classification, regression, clustering, and multivariate methods.
  • Expertise with relational data modeling and advanced SQL for data manipulation and performance optimization.
  • Experience working in an Agile/SCRUM environment
  • Strong problem-solving, analytical, and communication skills (written, verbal, and interpersonal).
  • Strong organizational skills, attention to detail, and ability to prioritize workload.
  • Professional presence with ability to take initiative, be creative, curious, and collaborative in a flexible, team-oriented environment.
  • Ability to independently conduct in-depth data analysis.
  • 3+ years in a professional data science role with proven track record of moving models from research to production.
  • 5+ years experience in professional data science role with advanced analytics applications.
  • Strong communication and presentation skills – ability to articulate technical challenges and solutions to diverse audiences.
  • Familiarity with retail, supply chain, digital & financial analysis, predictive analytics, and BI visualization toolsets.
  • Experience with DSML Automation platforms and MLOps tools.
  • Experience with Data Engineering/Cloud tools (Snowflake, BigQuery, AWS SageMaker), GenAI tools (Hugging Face, LangChain, LlamaIndex, OpenAI/Gemini APIs), and cloud-based BI and Analytics technologies.
  • Ability to work with minimal oversight while ensuring timely, accurate task completion.
Preferred Skills
  • Experience with DSML Automation platforms and MLOps tools.
  • Experience with Data Engineering/Cloud tools (Snowflake, BigQuery, AWS SageMaker), GenAI tools (Hugging Face, LangChain, LlamaIndex, OpenAI/Gemini APIs), and cloud-based BI and Analytics technologies.
Education
  • (Not required) – Bachelor's/Master's/Ph.D. in quantitative field (Computer Science, Statistics, Mathematics, Physics) or equivalent industry experience.