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BI Analyst

Job in Los Angeles, Los Angeles County, California, 90079, USA
Listing for: 829 Studios
Full Time position
Listed on 2026-10-02
Job specializations:
  • IT/Tech
    Business Intelligence, Data Analyst, Data Warehousing
Salary/Wage Range or Industry Benchmark: 80000 - 90000 USD Yearly USD 80000.00 90000.00 YEAR
Job Description & How to Apply Below

We are seeking a highly technical, data-driven BI Analyst to support a small number of high-value enterprise accounts. This role is built for someone who lives in large, complex datasets and turns them into clear, decision-grade insights. Working alongside an Account, Strategy and Media Directors, you will own the analytical layer for each assigned client - generating performance insights, producing forecasts, and surfacing the patterns that drive business outcomes.

You will operate fluently inside client-owned data warehouses such as Big Query, Snowflake, and Sigma, build BI environments in tools like Power BI/Tableau, and translate ambiguous business questions into structured analytical work. This role centers on developing a deep quantitative understanding of each client's business and using that fluency to inform strategy, investment, and forecasting decisions. The position plays a critical cross-functional role between Strategy, Paid Media, Client Services, and Analytics.

What

You'll Do

Data Analysis & Insight Generation

  • Synthesize large, multi-source datasets across paid media, web, CRM, ecommerce, offline conversions, and call tracking into clear performance narratives
  • Conduct deep-dive analyses on channel contribution, funnel efficiency, audience segmentation, LTV, CAC, MER, and cohort behavior
  • Surface hidden patterns, anomalies, and opportunities by applying statistical methods to complex, multi-dimensional datasets
  • Translate raw data into business-aligned insights tied to revenue, pipeline, retention, and growth outcomes
  • Partner with Strategy leadership to inform testing roadmaps, investment decisions, and budget reallocation

Forecasting & Predictive Modeling

  • Build and maintain forecasting models for revenue, spend, CAC, ROAS, CPA, and other KPIs across paid channels, ecommerce, and lead-gen environments
  • Develop scenario models (baseline vs. optimized) that project incremental opportunity from strategic shifts
  • Apply seasonality decomposition, time-series methods, and regression-based projection techniques
  • Quantify the financial impact of audit findings, optimization recommendations, and budget changes
  • Surface leading indicators of underperformance before they appear in lagging metrics

Business Intelligence & Data Visualization

  • Build and maintain BI environments using tools such as Power BI, Looker, Tableau, and Sigma
  • Design semantic data models, DAX measures, and reusable datasets that scale across clients and account types
  • Build executive-ready dashboards that translate complex datasets into clear, narrative-driven views of performance
  • Establish single-source-of-truth reporting frameworks that reconcile platform data with CRM and ecommerce truth
  • Optimize query performance, data refresh patterns, and cost efficiency across BI infrastructure

Working Within Client Data Environments

  • Operate fluently inside client-owned data warehouses, including Big Query, Snowflake, and Sigma, to query, model, and analyze marketing and business data
  • Write performant SQL against client schemas to build the datasets, views, and aggregations that power analysis and reporting
  • Develop attribution logic in the warehouse layer (multi-touch, last-click, position-based, custom blends) using whatever stack the client provides
  • Adapt to varying data architectures, naming conventions, and governance models across enterprise client environments
  • Partner with client data teams to align on definitions, source-of-truth logic, and access patterns
  • Support offline conversion pipelines via platform APIs (Google Ads, Meta CAPI) where data engineering input is required

Measurement Foundation & Data Integrity

  • Validate that conversion tracking, attribution logic, and data flow across Google Ads, Meta, Linked In, Tik Tok, GA4, and CRM environments feed the warehouse cleanly and consistently
  • Partner with tag management specialists to translate analytical requirements into data layer specifications
  • Identify discrepancies between platform reporting and source-of-truth, and trace them to root cause
  • Enforce consistent event taxonomies, UTM structures, and naming conventions at the data layer
  • Ensure analytical outputs respect privacy frameworks and consent management requirements

Cross-Functional Partnership

  • Act as the analytical counterpart to the Strategy Director or Enterprise Account Director on assigned enterprise accounts
  • Serve as the agency's go-to voice for diagnosing performance issues, sizing opportunities, and pressure-testing strategic hypotheses with data
  • Translate technical…
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