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sourceplanck

Data Analyst

Posted An Hour Ago
Remote
Hiring Remotely in United States
Junior
Remote
Hiring Remotely in United States
Junior
Collects, analyzes, and interprets complex data to support business decisions. Develops databases, data systems, processes, models, algorithms, dashboards, reports, and visualizations. Collaborates with business stakeholders, data scientists, and IT teams to solve business problems using statistical methods. Keeps current with analytics tools, technologies, and industry trends.
The summary above was generated by AI

 

 

 

We are seeking an experienced Data Analyst to join our team. The successful candidate will have a strong background in data analysis, excellent analytical and problem-solving skills, and the ability to work in a fast-paced environment.

 

Key Responsibilities:

 

1. Collect, analyze, and interpret complex data to inform business decisions.

2. Develop and maintain databases, data systems, and data processes.

3. Create data visualizations, reports, and dashboards to communicate insights to stakeholders.

4. Collaborate with cross-functional teams, including business stakeholders, data scientists, and IT professionals.

5. Develop and implement data models, algorithms, and statistical models to solve complex business problems.

6. Stay up-to-date with industry trends, emerging technologies, and new tools and methodologies.

 

Requirements:

 

1. Bachelor's degree in Computer Science, Statistics, Mathematics, or related field.

2. Advanced degree (e.g., MS) preferred.

3. Minimum 2 years of experience in data analysis or a related field.

4. Professional certifications, such as Google Data Analytics or Microsoft Certified: Data Analyst Associate.

5. Strong analytical, problem-solving, and communication skills.

6. Ability to work in a fast-paced environment.

7. Proficiency in data analysis tools, such as Excel, SQL, Tableau, or Power BI.

 

Nice to Have:

 

1. Experience with programming languages, such as Python, R, or Julia.

2. Knowledge of machine learning algorithms and statistical modeling.

3. Familiarity with cloud-based technologies, such as AWS or Azure.

4. Experience with data visualization tools, such as D3.js or Matplotlib.

 

 

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