Data Analyst

Data Analyst (H/F) - Role Overview

The Data Analyst (H/F)
is responsible for transforming raw data into actionable insights to support business decision-making, improve operational efficiency, and enhance overall performance. This role involves analyzing large sets of data from multiple sources, cleaning and validating data, and presenting findings through detailed reports and visualizations. The Data Analyst will work closely with various departments—such as marketing, finance, operations, and product teams—to identify trends, patterns, and key metrics that can drive business strategy.

Key responsibilities include data extraction, cleaning, and validation, as well as statistical analysis to identify key performance indicators (KPIs) and business trends. The Data Analyst will also create reports, dashboards, and visualizations that help stakeholders understand complex data and make informed decisions. Additionally, the role may involve running ad-hoc analyses, performing forecasting, and providing recommendations based on data-driven insights.

This position is ideal for someone with strong analytical skills, a keen attention to detail, and the ability to communicate complex data insights to both technical and non-technical audiences.

Qualifications

To be considered for the Data Analyst (H/F)
role, candidates should have a degree in data science, statistics, mathematics, computer science, economics, or a related field. Proficiency in data analysis tools such as Excel, SQL, and data visualization platforms (e.g., Tableau, Power BI) is required. Familiarity with statistical software (e.g., R, Python) is an advantage.

Key qualifications and skills for this role include:

• Data Analysis
  : Experience with analyzing large datasets to extract meaningful insights and identify trends. Strong statistical and analytical skills are essential.
• Data Visualization
  : Proficiency in creating visual reports and dashboards using tools like Tableau, Power BI, or Excel to present complex data in an understandable way.
• SQL & Database Management
  : Strong knowledge of SQL for querying and manipulating large datasets. Familiarity with database management systems (e.g., MySQL, PostgreSQL, or Oracle) is a plus.
• Statistical & Analytical Tools
  : Experience using statistical software and programming languages such as
  R
  or
  Python
  to conduct data analysis and build predictive models.
• Data Cleaning & Validation
  : Expertise in cleaning, transforming, and validating data to ensure its accuracy and integrity before analysis.
• Business Intelligence
  : Understanding key business metrics and how data can be used to optimize performance across various departments.
• Problem-Solving Skills
  : Ability to solve business problems by providing data-driven recommendations based on your analysis.
• Communication Skills
  : Strong written and verbal communication skills, with the ability to explain complex data insights to non-technical stakeholders in a clear and concise manner.
• Attention to Detail
  : High level of accuracy and precision when working with data to ensure the integrity and validity of analyses.

Certifications and Experience:

• Certifications
  : Relevant certifications in data analysis (e.g.,
  Google Data Analytics Certificate
  ,
  Microsoft Certified: Data Analyst Associate
  , or
  Certified Analytics Professional (CAP)
  ) can be an asset.
• Experience
  : Previous experience in a data analysis or related role is preferred. Experience with advanced data analysis techniques, machine learning, or predictive modeling is a plus but not required for entry-level positions.

Career Growth Potential:

The Data Analyst (H/F)
position offers significant career development opportunities. Over time, successful analysts can move into more senior positions such as
Senior Data Analyst
,
Business Intelligence Analyst
, or
Data Scientist
. The role can also lead to leadership positions in analytics, such as
Analytics Manager
or
Head of Data Science
.

• This role is an excellent fit for individuals looking to develop their expertise in data analysis while contributing to business success through actionable insights. It provides exposure to different areas of the business and allows for collaboration with teams across the organization, making it a key position in driving data-driven decision-making.