Data Analyst (H/F) Role DescriptionThe Data Analyst (H/F) is responsible for collecting, processing, and analyzing data to provide actionable insights that support business decisions and drive organizational growth. This role involves working with both structured and unstructured data from a variety of sources, identifying patterns, trends, and opportunities, and presenting the results in a clear and meaningful way. Data Analysts collaborate closely with different teams, including marketing, finance, operations, and product management, to help organizations optimize their processes and achieve their goals.Key responsibilities include:Data Collection & Processing : Gathering data from multiple internal and external sources, cleaning and preparing it for analysis, and ensuring that data is accurate and consistent.Data Analysis : Performing exploratory data analysis (EDA) to uncover trends, correlations, and anomalies, and applying statistical models and techniques to solve business problems.Reporting & Visualization : Developing and presenting reports, dashboards, and visualizations to help stakeholders easily understand the data and make informed decisions. Tools like Power BI, Tableau, or Excel may be used for this.Performance Tracking : Monitoring key performance indicators (KPIs) and providing regular updates to stakeholders on the performance of various business functions and campaigns.Forecasting & Predictive Analysis : Assisting with forecasting trends, identifying potential risks, and providing recommendations for future strategies based on data-driven insights.Collaboration : Working cross-functionally with teams like marketing, finance, and product development to provide data support for their projects and initiatives.The Data Analyst (H/F) plays a key role in transforming raw data into valuable insights, helping organizations make data-driven decisions that improve performance, increase efficiency, and drive growth.QualificationsCandidates for the Data Analyst (H/F) position typically hold a degree in Data Science, Statistics, Mathematics, Economics, Computer Science, or a related field. A strong understanding of data analysis techniques, statistical models, and the ability to use various tools to process and analyze data are essential for success in this role.Key qualifications include:Technical Skills : Proficiency in data analysis tools such as Microsoft Excel, SQL, R, Python, or other relevant programming languages.Data Visualization : Familiarity with tools like Power BI, Tableau, or Google Data Studio for presenting insights in a visual and easily digestible format.Statistical Knowledge : A solid understanding of statistical techniques, hypothesis testing, and data sampling methods to draw meaningful insights from large datasets.Attention to Detail : High level of accuracy in data entry, cleaning, and processing to ensure the reliability of results.Problem Solving : Strong analytical skills and the ability to approach complex business problems with data-driven solutions.Communication Skills : The ability to communicate complex findings clearly to both technical and non-technical stakeholders, making insights actionable for business teams.Time Management : Ability to manage multiple tasks and projects, prioritize effectively, and meet deadlines.Experience with data management platforms, cloud services (AWS, Azure), and a basic understanding of machine learning or predictive modeling is advantageous, but not always required. Knowledge of data privacy regulations (e.g., GDPR) is also a plus, as the role may involve working with sensitive data.Ideal CandidateThe Data Analyst (H/F) role is ideal for someone who enjoys working with data, solving complex problems, and transforming numbers into insights that drive business decisions. The ideal candidate will have strong technical skills, a passion for learning new tools and techniques, and a collaborative mindset to work across teams. This position offers an exciting opportunity to contribute to the organization's data strategy, helping shape its future direction based on solid, data-driven evidence.