Senior Data Analyst, Finance Analytics

Data and Analytics Santa Monica, California New York City, New York

Description

SUMMARY

We are looking for an experienced Senior Data Analyst to join our Finance Analytics team to support the design, build and testing of business forecasting and reporting. This role requires acute attention to detail, a strong sense of accountability, collaboration skills, and extensive hands-on experience with reporting and communicating data. You will be working on data analysis, KPI definitions, data investigations and the delivery of organized insights and ideas for rapid and clear communication.

The Finance Analytics function masters data analysis, advanced reporting, data modeling and visualizations that serve the dual purpose of analytically supporting the Disney Streaming Finance organization and delivering fact-based actionable recommendations. Through the creation of forecasting, LTV, and ARPU models, this team leads the analytical support for various business decisions. Finance, Product, Marketing, Engineering and Data Science teams will be your partners to execute on innovative methods and best-in-class practices that power all of our improvements.

WHAT YOU'LL DO 

  • Create, deliver, and continuously improve our business measurement solutions
  • Partner closely with finance stakeholders to identify and unlock opportunities to better forecast and report on business performance
  • Manage forecasting, Lifetime Value (LTV), and ARPU modeling and development in collaboration with Data Science teams
  • Understand the systems and business processes that populate critical systems with data
  • Work with stakeholders to outline and define data definitions and apply appropriate usage
  • Analyze and report key data quality health KPIs through regular metric monitoring and revise as needed as the number of datasets and critical systems expand
  • Translate complex reporting needs into technical specifications, including calculations, custom groups, parameters, filtering criteria and/or aggregations
  • Analyze subscriber and behavior data to identify patterns, uncover opportunities, and create common understanding of how people are interacting with the platform and content
  • Build forecasting tools and automate reports and dashboards that provide insights into business measurement and effectiveness
  • Build intuitive presentations, interfaces, infographics and visualizations to tell stories with data
  • Provide ongoing reporting and analysis to inform and support business, product, and marketing decisions

WHAT YOU'LL BRING

  • 4+ years of hands-on analytical work experience with SQL and/or Python
  • Expert proficiency in conducting analysis using SQL
  • Experience with Lifetime Value (LTV) modeling and business performance forecasting and comfortable working in collaboration with Engineering and Data Science teams
  • High familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, Redshift, Airflow
  • Expertise manipulating large data sets, interpreting data trends, and using a multitude of disparate data sources and tools
  • Strong analytical skills with the ability to apply business strategy to data analysis and recommendations
  • Strong experience in documenting the data requirements, data strategy, data rules (standardization, cleanse, and validation)
  • Perform root-cause analysis to identify patterns in financial and customer data sets, including subscriber acquisition and retention metrics
  • Strong analytical and technical skills to troubleshoot issues, analyze the cause, quickly come-up with the possible solutions, document the changes, and communicate organizational impact
  • Ability to evaluate risks and provide recommendations in a timely manner
  • Explain data anomalies, develop data visualizations and reporting to drive key messaging and recommendations
  • Familiarity with data exploration and data visualization tools like Tableau or Looker
  • Ability to think strategically, analyze and interpret market and consumer information

NICE-TO-HAVES

  • Experience in the streaming media industry or other subscription-based service
  • Experience in the technology industry, knowledge of data products
  • Python experience writing, managing, and deploying code
  • BA or BS in a quantitative field (Business, Math/Statistics, Economics, CS, Engineering, or similar) is desired

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