Data Scientist: End-to-End ML & AI Solutions

Skechers U.S.A., Inc.; Manhattan Beach, Northern (CA, KY); Hybrid; USD 95,000 - 130,000; Full time

Job summary

Skechers U.S.A., Inc. is seeking a Data Scientist to join the Data and Analytics team in a hybrid capacity. You will build advanced analytics solutions, develop ML models, and translate complex data challenges into production-ready tools.

Collaboration with data stewards and business leads will be essential to deliver scalable insights. You’ll work with Python, Spark, and ML frameworks to create impactful analytics, leveraging DSML and MLOps practices to keep models robust and useful for

Qualifications

• Bachelor's/Master's/Ph.D. in quantitative field or equivalent experience.
• 3+ years in professional data science with production-ready models.
• 5+ years in data science with analytics applications preferred.
• Strong communication and ability to present to diverse audiences.
• Experience with retail, supply chain, and BI visualization toolsets.
• Experience with DSML automation platforms and MLOps tools.
• Familiarity with Data Engineering/Cloud tools and GenAI platforms.

Responsibilities

• End-to-end ML development from ideation to production.
• Develop and deploy models with reliable data pipelines.
• Leverage LLMs and RAG to enhance data products and workflows.
• Write production-grade code and collaborate with data engineers.
• Monitor model drift, bias, and performance over time.
• Conduct experiments, A/B testing, and causal inference studies.

Skills

Python

Spark

ML frameworks

SQL

Data storytelling

Analytical thinking

Communication

Education

Bachelor's / Master's / PhD in quantitative field

Tools

Snowflake

BigQuery

AWS SageMaker

Hugging Face

LangChain

LlamaIndex

OpenAI APIs

Job description

Skechers U.S.A., Inc. is seeking a Data Scientist to join the Data and Analytics team in a hybrid capacity. You will build advanced analytics solutions, develop ML models, and translate complex data challenges into production-ready tools.

Collaboration with data stewards and business leads will be essential to deliver scalable insights. You’ll work with Python, Spark, and ML frameworks to create impactful analytics, leveraging DSML and MLOps practices to keep models robust and useful for