Data Analyst ANZSCO 224114
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Data Analyst ANZSCO 224114
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UNIT GROUP: 2241
Data Analyst
Data Analysts are professionals responsible for collecting, processing, and statistical analysis of enormous amounts of data to identify trends, patterns, and insights to inform business decision-making. They play a key role in making raw data workable to enable informed decisions by applying various analytical tools and techniques. Data Analysts work with business stakeholders to determine their data needs and provide accurate, timely, and relevant information to inform decision-making and strategic planning.
Occupation List:
489 (S/T) Occupations List
482 TSS Visa Medium Term List
407 Training Visa Occupations List
482 TSS Visa Regional Occupation List
189 Skilled Independent and Family Sponsored
489 Occupations List and 485 Graduate Work Stream
190 State/Territory Sponsored
186 ENS Visa Occupations List
187 RSMS Visa Occupations List
491 Skilled Work Regional (Provisional) Visa (subclass 491) Occupation List
494 Skilled Employer Sponsored Regional (Provisional) Visa (subclass 494)
Employer Sponsored Stream
Not on the occupation Lists
482 TSS Visa Short Term List
Skill Level
A bachelor’s degree in computer science, mathematics, statistics, data science, or a similar field is typically required. In some cases, relevant work experience (up to five years) is acceptable in lieu of formal qualifications. Knowledge of software packages such as SQL, Excel, or similar data analysis software, and knowledge of statistical analysis techniques, can significantly improve job opportunities.
English Requirement
In order to qualify for a visa, applicants must demonstrate English proficiency in one of the following tests:
IELTS: At least 6 in Writing, Listening, and Reading; 7 in Speaking; and 7 overall.
OET: At least grade B in all categories.
TOEFL iBT: At least 12 in Listening, 13 in Reading, 21 in Writing, 23 in Speaking, and overall score of 93.
PTE Academic: 50 minimum in Writing, Reading, and Listening; 65 in Speaking; overall score of 65.
Tasks to Perform
Data Collection and Data Preparation: Collect data from various sources and clean, organize, and prepare data for analysis by removing errors, duplicates, or inconsistencies.
Data Analysis: Perform statistical and quantitative analysis to identify trends, correlation, and patterns in big data utilizing techniques such as regression, clustering, and hypothesis testing.
Data Visualization: Create charts, graphs, and dashboards to present data findings and make them visually engaging and understandable for business stakeholders.
Report Generation: Create reports of data analysis outcomes, results, and actionable recommendations to support decision-making and business strategy development.
Business Intelligence: Enable business operations by providing data-driven insights that enable the identification of areas for optimization and efficiency improvements.
Statistical Modeling: Apply statistical models and techniques to solve hard business issues such as demand forecast, customer division, or risk assessment.
Database Querying: Develop SQL or any other query language to retrieve and manipulate information stored in databases in order to supply analysis and report needs.
Trend Analysis: Conduct trend analysis to observe the performance of companies over time and suggest on the basis of the trends of the data.
Stakeholder Engagement: Work hand in hand with departments and business units to understand their data needs and translate them into effective analytical models and solutions.
Process Improvement: Identify inefficiencies or issues in business processes through data analysis and recommend improvements to increase productivity, reduce costs, or enhance customer experience.
Data Integrity and Accuracy: Verify data utilized in analysis to be accurate, good quality, and consistent through enactment of best practices for data management and validation.
Data Privacy and Security: Comply with data privacy regulation and internal policy such that individual and sensitive information is handled safely and responsibly.
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