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Home Malaysia Data Analyst

Data Analyst

Full time at Talentbank in Malaysia
Posted on September 5, 2024

Job details

Responsibilities

  • Data Collection: Gathering data from various sources, such as databases, spreadsheets, APIs, and other relevant sources. This could involve extracting data, cleaning it, and preparing it for analysis.
  • Data Cleaning and Preprocessing: Ensuring the data is accurate, consistent, and free of errors or inconsistencies. This step often involves dealing with missing data, handling outliers, and transforming data into a suitable format for analysis.
  • Data Analysis: Using statistical and analytical techniques to identify patterns, trends, and correlations in the data. This may involve performing exploratory data analysis, hypothesis testing, and creating visualisations to present findings effectively.
  • Reporting and Visualization: Presenting your analysis and insights to stakeholders in a clear and understandable manner. This could involve creating charts, graphs, dashboards, and reports to communicate the results of your analysis.
  • Business Insights: Translating data-driven findings into actionable recommendations that can help improve business processes, enhance decision-making, and achieve organisational goals.
  • Data Management: Ensuring data security, privacy, and compliance with relevant regulations. Data analysts may also play a role in maintaining databases and data infrastructure.
  • Collaboration: Working closely with other team members, such as data scientists, business analysts, and stakeholders, to understand requirements and provide support in data-related matters.
  • Continuous Learning: Staying updated with the latest tools, technologies, and methodologies in data analysis to improve skills and efficiency.
Requirements
  • Advanced degree in Data Science, Statistics, Computer Science, or a related field, with a strong foundation in quantitative analysis.
  • Proven experience as a Data Analyst, with expertise in data mining, machine learning, and statistical analysis.
  • Proficiency in data science tools and programming languages (e.g., Python, R, SQL) and experience with data visualization tools (e.g., Tableau, Power BI).
  • Strong problem-solving skills and the ability to work independently on complex analysis.
  • Excellent communication skills, with the ability to present data and insights in a clear, concise manner to both technical and non-technical stakeholders.
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