Data Analyst

Posted 4 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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