Data Mining Analyst - Flexible Hours, Visa Support & Growth

Qatar Wellness Network; Herning; On-site; DKK 63,000 - 86,000; Full time

Benefits offered by this job

Flexible working hours

Accommodation provided

Career growth opportunities

Visa support

Job summary

Qatar Wellness Network is seeking a Data Mining Analyst to join our team in Herning, Denmark. You will collect, organize, and analyze large data sets to identify patterns and trends that guide business decisions.

Collaborate with cross-functional teams to develop data-driven solutions, present findings clearly, and monitor data quality to ensure accuracy and reliability in ongoing projects.

Qualifications

• Bachelor's degree in Data Science, Statistics, Mathematics or related field.
• 2+ years of experience in data mining or related role.
• Strong knowledge of SQL and programming languages such as Python or R.
• Experience with data visualization tools such as Tableau or Power BI.
• Knowledge of machine learning techniques is a plus.
• Excellent analytical skills with the ability to manipulate and interpret complex datasets.
• Attention to detail with a strong focus on accuracy.

Responsibilities

• Collect and organize large sets of data from various sources
• Develop and implement data mining models and algorithms
• Identify patterns and trends in the data to provide actionable insights
• Collaborate with cross-functional teams to understand business needs and develop data-driven solutions
• Present findings and recommendations in a clear and concise manner
• Continuously monitor data quality to ensure accuracy and reliability

Skills

SQL

Python

R

Tableau

Power BI

Machine learning

Education

Bachelor's degree in Data Science, Statistics, Mathematics or related field

Tools

Tableau

Power BI

Job description

Qatar Wellness Network is seeking a Data Mining Analyst to join our team in Herning, Denmark. You will collect, organize, and analyze large data sets to identify patterns and trends that guide business decisions.

Collaborate with cross-functional teams to develop data-driven solutions, present findings clearly, and monitor data quality to ensure accuracy and reliability in ongoing projects.