Senior Data Scientist

Hybrid Glendale, CA

Our client seeks a Senior Data Scientist to develop and deploy machine learning solutions that drive business value across studio operations. The role combines hands‑on model development with production deployment, partnering with engineering to build scalable and maintainable ML systems. The ideal candidate has deep machine learning expertise, strong Python skills, and experience operationalizing models in production environments.

Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

Rate: $107.00 to $110.00/hr. w2

JN -

• Design, build, and deploy machine learning models to solve complex business challenges.
• Develop predictive models, forecasting solutions, and statistical analyses.
• Identify trends, patterns, and insights from large datasets.
• Create AI/ML solutions that support business objectives.
• Monitor and optimize ML model performance.
• Own the full data science lifecycle from data acquisition through deployment.
• Perform feature engineering, selection, and model development.
• Create visualizations and present insights to stakeholders.
• Translate analytical findings into actionable recommendations.
• Deploy and operationalize machine learning models in production.
• Build scalable, repeatable, and maintainable ML pipelines.
• Partner with engineering on architecture and implementation.
• Support MLOps practices and model lifecycle management.
• Contribute to Snowflake-based data and analytics ecosystems.
• Collaborate across engineering, analytics, and business teams.
• Provide technical guidance and mentorship.
• Communicate findings and recommendations to leadership.
• Stay current on emerging AI/ML technologies and industry trends.

• 5+ years of data science experience delivering production solutions.
• Strong Python programming skills.
• Expert experience with scikit-learn, pandas, and Num Py.
• Deep understanding of ML algorithms, statistics, and predictive modeling.
• Experience building and deploying production ML pipelines.
• Snowflake experience.
• Data storytelling and visualization skills.
• Problem‑solving and communication abilities.
• Preferred:
  Master’s degree in a related field.
• Preferred:
  Financial forecasting experience.
• Preferred:
  Databricks or Big Query experience.
• Preferred:
  Experience with dbt and Airflow.
• Preferred:
  Streamlit experience.
• Preferred:
  Experience building scalable AI/ML platforms.

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or related quantitative field.