Data Scientist ( Los Angeles-California )
About The Position
The Data Scientist will develop AI/ML solutions to support the company’s mission of creating innovative and engaging content. The role covers the end-to-end machine learning lifecycle, including data collection, feature generation and selection, algorithm development, forecasting, visualization, communicating results, and deploying and maintaining models. The candidate will design analytical solutions for financial and operational use cases and help build repeatable, maintainable, and scalable production ML systems in collaboration with engineering and data teams. The role also includes monitoring model performance, staying current with AI/ML technologies, and providing technical guidance to other engineers.
Requirements
- At least 5 years of experience in data science, with a track record of delivering successful projects.
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related quantitative field.
- Proficiency in Python, R, or Scala; Python is identified as a must-have skill.
- Expert-level experience with scikit-learn, NumPy, pandas, and other ML libraries.
- Solid understanding of machine learning technologies, models, mathematics, and statistical methods.
- Experience building and deploying full-stack ML pipelines, including data extraction, data mining, model training, feature development, testing, and deployment.
- Demonstrated machine learning expertise and experience building ML models.
- Data-driven storytelling and data visualization skills for communicating insights to business leaders and technical stakeholders.
- Strong problem-solving skills and creative thinking.
- MLOps experience is identified as a must-have skill.
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 such as dbt and Airflow and UI layers such as Streamlit.
Responsibilities
- Develop novel AI/ML solutions and machine learning models.
- Architect efficient data models and high-quality production pipelines, partnering with Engineering on necessary telemetry.
- Design, build, and deploy predictive models, machine learning algorithms, and statistical analyses for business challenges.
- Identify trends, patterns, and insights in large datasets to inform decisions.
- Work across data collection, feature generation and selection, algorithm development, forecasting, visualization, and communication of model results.
- Monitor and maintain ML model performance.
- Research current AI/ML trends and technologies.
- Provide technical guidance and mentorship to other engineers.
- Collaborate with data engineering teams to support data quality and accessibility.
- Communicate insights and best practices to leadership.
- Support financial and operational business use cases and design advanced analytical solutions.
- Deploy machine learning solutions, support MLOps, and work with engineering teams to create repeatable, maintainable, and scalable solutions.
- Contribute to Snowflake-based environments.
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What This Job Offers
Career Level
Senior
