> Markdown version of [/jobs/ext/3605786-data-scientist](https://www.wearedevelopers.com/jobs/ext/3605786-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** KellyMitchell - **Location:** Glendale, CA, United States (Remote available) - **Experience:** Expert - **Salary:** $208,000.0 - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Airflow, Algorithm Design, Big Data, BigQuery, Cloud Database, Information Engineering, Data Mining, Data Presentation, Python (Programming Language), Machine Learning, NumPy, Data Processing, Feature Engineering, Snowflake, Pandas, Scikit Learn, Information Technology, Machine Learning Operations, Streamlit Framework, Databricks - **Published:** October 7, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/ppldldxmic ## About the Role * Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related quantitative field * 5+ years of experience in data science, with a track record of delivering successful projects * Machine Learning experience * Python * Snowflake * MLOps experience * Proficiency in programming languages such as Python, R, or Scala * Expert-level experience working with scikit-learn, numpy, and pandas and other ML libraries * Solid understanding of ML technologies, models, mathematics and statistical methods * Expert data-driven storytelling skills to convey insights to business leaders and technical stakeholders and to drive impactful decisions, with an eye for great ways to visualize data * Experience building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deployment * Machine learning expertise was repeatedly identified as the most important qualification * Candidates should clearly demonstrate experience building ML models Preferred Skills/Experience (Nice-to-Haves) * Master's degree * Experience with financial forecasting models * Experience with cloud databases, such as Snowflake, databricks, and BigQuery * Familiarity with data processing tools like dbt and Airflow, UI layers like Streamlit is a big plus Key Competencies & Behaviors * Advanced Analytical Solutions * Technical guidance and mentorship * Excellent problem-solving skills and the ability to think creatively * Research and stay up-to-date on the latest AI/ML trends and technologies ## Description Our client, a leading entertainment provider, is seeking a Senior Data Scientist to join their team! This position is a 1 year contract, hybrid 2-4 days onsite in Glendale, California. This position is W-2 only. We do not work with third-party firms or C2C arrangements for this role. Core Responsibilities * Develop novel AI/ML solutions to further the company's mission of creating innovative and engaging content * Architect efficient data models and high-quality production pipelines and partner with Engineering for all necessary telemetry * Design, build, and deploy predictive models, machine learning algorithms, and statistical analyses to address complex business challenges * Identify trends, patterns, and insights from large datasets to inform decision-making * Work end to end from data collection, feature generation and selection, algorithm development, forecasting, visualization and communicating of model results * Think creatively to solve complex problems * Monitor and maintain the performance of ML models * Research and stay up-to-date on the latest AI/ML trends and technologies * Provide technical guidance and mentorship to other engineers * Collaborate with data engineering teams to ensure the quality and accessibility of data * Communicate insights and best practices in leadership * Develop machine learning models * Support financial and operational business use cases * Design advanced analytical solutions * Deploy machine learning solutions * Support ML Operations (MLOps) * Work with engineering teams * Create solutions that are repeatable, maintainable, and scalable * Contribute to Snowflake-based environments