Senior Data Scientist — Hybrid, ML Leader in Entertainment

KellyMitchell Group; Glendale (CA); Hybrid; USD 96,000 - 138,000; Full time

Benefits offered by this job

Medical, Dental, & Vision Insurance

Employee-Owned Profit Sharing (ESOP)

401K offered

Job summary

KellyMitchell Group is seeking a Senior Data Scientist for a 1-year contract in Glendale, CA. Hybrid work arrangement with 2-4 days onsite; W-2 only; no third-party or C2C.

The role requires 5+ years of data science experience, strong ML background, and proficiency in Python and Snowflake. Responsibilities include building AI/ML solutions, end-to-end ML pipelines, and collaboration with engineering and data teams.

Qualifications

• Bachelor’s degree in a quantitative field.
• 5+ years of data science experience delivering projects.
• Proficiency in Python and ML libraries (scikit-learn, numpy, pandas).

Responsibilities

• Develop novel AI/ML solutions to advance content.
• Architect data models and production pipelines with telemetry.
• Design and deploy predictive models and ML algorithms.
• Analyze large datasets to identify trends and insights.
• End-to-end ML workflow: data collection, features, training, deployment.
• Monitor model performance and stay current with AI/ML trends.
• Provide technical guidance to engineers.
• Collaborate with data engineering to ensure data quality.
• Communicate insights to leadership.
• Contribute to Snowflake-based environments.

Skills

Python

Machine Learning

R/Scala

Data storytelling

Data analysis

Education

Bachelor’s degree in a quantitative field

Master’s degree

Tools

Snowflake

Databricks

BigQuery

dbt

Airflow

Streamlit

Job description

KellyMitchell Group is seeking a Senior Data Scientist for a 1-year contract in Glendale, CA. Hybrid work arrangement with 2-4 days onsite; W-2 only; no third-party or C2C.

The role requires 5+ years of data science experience, strong ML background, and proficiency in Python and Snowflake. Responsibilities include building AI/ML solutions, end-to-end ML pipelines, and collaboration with engineering and data teams.