Remote Data Analytics Graduate Jobs in California

Job Location - Remote (Support EST Time Zone)

Type - Contract (12 Months)

Pay Rate - $50.00 - $56.00 Per Hour (W2 Only)

Candidates must be able to work on a W2 basis. C2C / Sponsorship is not available.

Summary -

The Marketing Intelligence team helps optimize and plan media campaigns for 30+ TV networks streaming products, Theatricals and Games.

The business encompasses both off-channel acquisition and on-channel retention marketing efforts, which have seen exponential growth in data collection and management. Join a data-driven team that is building a marketing intelligence discipline incorporating big data sets, automation and visualizations to drive media efficiencies and effectiveness.

The Big Data Analyst will lead the scoping and ongoing validation of data pipelines, analytical models, and self‑service dashboards. They will guide analysts in best practices for data querying, modeling, and visualization. This role works closely with data engineering and data science teams to strengthen data infrastructure and analytical capabilities, with a focus on defining data standards and business logic used to join and process data. The Big Data Analyst will also oversee downstream data outputs and ensure their availability and data integrity within visualization tools.

This position is ideal for someone who loves big data, enjoys building scalable analytical solutions, and wants to shape the data infrastructure of a modern marketing intelligence organization.

Responsibilities

Big Data Analytics & Modeling

• Lead the querying, mining, and analysis of large datasets-including Smart TV, media exposure, cost, and viewership data-to support marketing performance and attribution measurement.
• Manage analytics roadmap for cross-platform viewership across linear TV and Streaming platforms.
• Guide the application of statistical modeling techniques for audience segmentation, attribution, media mix modeling, and marketing optimization.
• Ensure analytical outputs are accurate, reproducible, and aligned with business needs.
• Support the translation of analytical projects into scalable, automated data products and repeatable workflows.
• Leverage AI tools and platforms to engineer prompts, develop custom agents, and drive workflow automation across team operations

Data Infrastructure & Engineering Collaboration

• Partner with data engineering teams to access, combine, and validate structured and unstructured data sources.
• Contribute to the development and maintenance of data models, pipelines, and analytical frameworks.
• Create data dictionaries for raw data inputs and define how business logic should be applied for reporting, modeling and attribution outputs.
• Ensure data lifecycle governance best practices are followed across collection, access, and storage and support business objectives and goals.
• Oversee data quality, version control, and documentation standards for the analytics team.
• Leverage AI tools to automate data processing, enhance analytical workflows, and identify opportunities for improved efficiency and insight generation.

Cross Functional Coordination

• Translate business questions into clear analytical requirements for the team.
• Coordinate with marketing, research, and subscriber acquisition teams to ensure analytical tools support business operational needs and KPIs.
• Support ad hoc analytical projects and evolving business priorities.
• Manage data privacy and legal requirements for marketing use cases.

Must Have Skills

SQL experience

3+ years; Data Query building expertise, partnering with engineers in previous roles.

Data prep for Data Analytics

3+ years; Working with Big Datasets for end-use for data visualization or analysis.
Experience working with ETL Data Workflows

3+ years; Extract, transform, and load disparate data sets from various platforms (internal and external data sources).

Nice to Have Skills

• Experience with AI prompt engineering and building agents using platforms such as Claude or GPT is a plus
• Familiarity with viewership datasets (Nielsen, Inscape, Samba, STB data) is a plus.

Soft Skills:

• Understanding of data lifecycle management and da