Senior Data Analyst

Posted 2024-09-25

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💎 Seniority level: Senior, 2+ years

📍 Location: United States

💸 Salary: $80,000 - $105,000 per year

🔍 Industry: E-commerce, retail, and entertainment

🏢 Company: Wpromote👥 501-1000💰 $ Private on 2022-10-26Advertising SEO Marketing SEM

🗣️ Languages: English

⏳ Experience: 2+ years

🪄 Skills: PythonSQLData AnalysisData MiningGitData analysisData miningCommunication 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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