We’re looking for a Data Scientist to develop data-driven insights and tools that enhance user experiences and inform business decisions. In this role, you’ll apply analytics, machine learning and AI to uncover patterns, build predictive models, and deliver scalable solutions that drive measurable impact.

You’ll collaborate with data engineers, analysts, and product managers across the organization to deliver end-to-end projects—from exploration and modeling to deployment and performance monitoring—helping to strengthen our data-first culture and support strategic decision-making.

Responsibilities

Design, develop, and deploy models, algorithms, and data-driven solutions that address business and product needs.
Apply statistical and machine learning techniques to improve user engagement, drive subscription growth, and evaluate product performance.
Conduct exploratory data analysis and performance evaluation to ensure model accuracy and reliability.
Collaborate with data engineers, analysts, and stakeholders to integrate data science solutions into production systems and workflows.
Develop clear visualizations, reports, and presentations that communicate insights to technical and non-technical audiences.
Support experimentation and A/B testing by designing experiments and interpreting results to guide decision-making.
Maintain documentation, reproducibility, and version control best practices for all deliverables.
Stay current with emerging tools, methodologies, and techniques in data science to continuously improve the team’s capabilities.
Other duties as assigned.

Requirements

Bachelor’s degree or higher in Data Science, Statistics, Computer Science, or a related STEM field. With a bachelor’s degree 3+ years of relevant industry experience in data science roles, OR 1+ with a master’s or PhD degree.
Demonstrated experience building and evaluating predictive models using statistical and machine learning methods.
Proficiency in Python (e.g., pandas, scikit-learn) and SQL.
Experience working with cloud-based platforms such as AWS, GCP, or Azure for data storage and compute.
Knowledge of software development practices including version control, model tracking, and deployment tools (e.g., Docker, CI/CD, MLflow).
Strong analytical and problem-solving skills with the ability to translate data insights into business recommendations.
Excellent written and verbal communication skills; ability to present findings to both technical and non-technical audiences.

Preferred Qualifications

Experience with media, digital publishing, or subscription-based products.
Familiarity with recommendation systems or personalization models.
Experience with A/B testing design and interpretation.
Exposure to LLM applications or natural language processing frameworks (e.g., Hugging Face, AWS Bedrock).
Familiarity with dbt or analytics engineering best practices.

The L.A. Times is an equal opportunity employer and welcomes all qualified applicants regardless of race, ethnicity, religion, gender, gender identity, sexual orientation, disability status, protected veteran status, or any other characteristic protected by law. We actively work to create an inclusive environment where all of our employees can thrive. This Privacy Notice for Los Angeles Times sets forth how we will use the information we obtain when you apply for a position with us. Explore our company history, achievement, values, mission and more on our career site.

The pay scale the Company reasonably expects to pay for this position at the time of the posting is $120,000 to $140,000 and takes into account a wide range of factors including but not limited to skill set, experience, training, licenses, certifications, and other business or organizational needs. Compensation will be determined based on the above factors along with the requirements of the position. At the L.A. Times, it is not typical for an individual to be hired at or near the top of the range for the role. Please visit our career site to view the benefits available to our employees. We recommend adding our applicant tracking system domain (@dayforce.com) as a safe sender or contact, sometimes these emails get filtered to candidates' spam folders.

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