Data Mining Analyst: Turn Big Data into Clear Insights

Work standard

Khanpur

Hybrid

PKR 2,778,000 - 3,705,000

Full time

14 days+

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Job summary

Work standard is seeking a Data Mining Analyst in Khanpur to collect, clean, and analyze large datasets, identify patterns, and develop insights using SQL, Python, and Tableau. You will create visualizations and reports to inform business decisions and collaborate with team members to interpret results.

The role requires strong analytical skills, a math/CS background, and the ability to communicate complex findings to non-technical stakeholders.

Qualifications

  • Bachelor's degree in Mathematics, Statistics, Computer Science or a related field.
  • Proven experience with data mining techniques and tools (e.g. SQL, Python).
  • Strong analytical skills with the ability to collect, organize and analyze large datasets.
  • Knowledge of statistical analysis methods (e.g. regression analysis).
  • Familiarity with visualization tools (e.g. Tableau).
  • Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders.

Responsibilities

  • Collecting, cleaning, and organizing large datasets.
  • Using statistical software/tools to analyze data.
  • Identifying patterns, trends, and correlations in the data.
  • Creating visualizations and reports to present findings.
  • Collaborating with other team members to interpret results.
  • Communicating complex data findings in a clear and concise manner.

Skills

SQL
Python
Data mining
Statistical analysis
Tableau
Communication

Education

Bachelor's degree

Tools

Tableau

Job description

Work standard is seeking a Data Mining Analyst in Khanpur to collect, clean, and analyze large datasets, identify patterns, and develop insights using SQL, Python, and Tableau. You will create visualizations and reports to inform business decisions and collaborate with team members to interpret results.

The role requires strong analytical skills, a math/CS background, and the ability to communicate complex findings to non-technical stakeholders.

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