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Senior Data Analyst

Posted 4 months agoViewed

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πŸ’Ž Seniority level: Senior, 2+ years

πŸ“ Location: United States

πŸ’Έ Salary: $80,000 - $105,000 per year

πŸ” Industry: E-commerce, retail, and entertainment

🏒 Company: WpromoteπŸ‘₯ 501-1000πŸ’° Private over 2 years agoAdvertisingSEOMarketingSEM

πŸ—£οΈ Languages: English

⏳ Experience: 2+ years

πŸͺ„ Skills: PythonSQLData AnalysisData MiningGitCommunication Skills

Requirements:
  • Excellent analytical and problem-solving skills with strong attention to detail.
  • Critical thinking: the ability to look at numbers, trends, and data and come to new conclusions based on the findings.
  • Excellent foundational math/statistical skills with the ability to juggle facts, figures, and number crunching.
  • Strong communication skills, with experience in creating and delivering presentations and executive summaries.
  • 2+ years of hands-on data analysis experience within an agency or in-house environment.
  • Advanced programming skills (R or Python) for data cleaning, data modeling, building pipelines, API calls, etc.
  • Advanced experience in SQL (i.e.: window functions, stored procedures, and views, Triggers, Unions, CTEs, subqueries, debugging).
  • Intermediate to advanced competency in statistics, probability, and linear algebra.
  • Advanced Excel and/or Google Sheets skills.
  • Experience/familiarity with version control (i.e.: Git, Bitbucket, etc.).
  • An interest or passion for marketing analytics.
  • Bachelor’s degree in a quantitative field (Stats, Mathematics, CS, Information Technology, Economics, Engineering, etc.).
Responsibilities:
  • Interpreting, presenting, and communicating results by creating presentations and/or dashboards that communicate a succinct and compelling business story, driving decisions through research results.
  • Learning to transform, improve, and integrate data, depending on the business requirements.
  • Planning and scoping end-to-end data analysis projects by identifying the business problem and selecting appropriate investigative testing and solutions.
  • Using SQL and BigQuery to combine data sets across multiple sources.
  • Delivering the data in a useful and appealing way to technical and non-technical audiences using Looker.
  • Working across various departments to understand client needs.
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