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Data Analyst

Posted 2 months agoViewed

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💎 Seniority level: Middle, At least three years

📍 Location: US, Canada, Europe

💸 Salary: 140000 - 160000 USD per year

🔍 Industry: AI and machine learning

🏢 Company: RunPod, Inc.

🗣️ Languages: English

⏳ Experience: At least three years

🪄 Skills: PythonSQLData AnalysisSnowflakeTableauData scienceCommunication SkillsAnalytical SkillsCollaborationData visualization

Requirements:
  • Bachelor’s degree in Data Science, Statistics, Computer Science, or a related field. A Master’s degree is a plus.
  • At least three years of experience in a data analytics role, preferably with user and machine data exposure.
  • Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
  • Proficiency in data analysis tools and programming languages such as SQL, Python, and R.
  • Experience with data visualization tools (e.g., Mode, Tableau, or Power BI).
  • Experience with data warehousing platforms (e.g., Snowflake, Athena, or Redshift).
  • Excellent verbal and written communication skills, with the ability to translate complex data into actionable insights.
  • Strong problem-solving skills.
  • Successful completion of a background check.
Responsibilities:
  • Analyze large, complex datasets to extract actionable insights about users, product performance, and operational efficiency.
  • Work closely with cross-functional teams, including engineering, marketing, operations, and sales, to support data-driven decision-making.
  • Develop and implement data collection systems and strategies that optimize statistical efficiency and data quality.
  • Identify, analyze, and interpret trends or patterns in complex data sets.
  • Prepare reports and dashboards that use relevant data to communicate trends, patterns, and predictions.
  • Collaborate with engineering teams to enhance data collection and analysis processes.
  • Present findings and recommendations to stakeholders and executive leadership clearly and compellingly.
  • Stay abreast of industry trends and best practices in data analysis and data science.
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