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Data Analyst
Description
Overview
The Data Analyst will be responsible for analysing large amounts of data and providing insights that will drive business decisions. This role will require a strong understanding of data analysis tools, techniques and methodologies as well as the ability to communicate findings to non-technical stakeholders.
Responsibilities
- Collect, analyse, and interpret large datasets using statistical techniques
- Develop visualisations and dashboards to communicate insights and findings
- Collaborate with cross-functional teams to identify business opportunities
- Provide recommendations to improve performance
- Monitor and analyse key performance indicators to measure the effectiveness of business strategies
- Develop and maintain data models and databases to support business needs
- Automate data collection, processing, and analysis workflows to increase efficiency and accuracy
- Stay up-to-date with industry trends and best practices in data analysis and visualisation
Qualifications
- Bachelor’s degree in Mathematics, Statistics, Computer Science or related field
- Strong analytical and problem-solving skills
- Proficiency in SQL, Python or R programming languages
- Experience with data visualisation tools such as Tableau, PowerBI or Looker
- Excellent communication and presentation skills
- Experience with big data technologies such as Hadoop or Spark
- Familiarity with machine learning algorithms and techniques
- Knowledge of data warehousing and ETL processes
- Understanding of database design and management principles
- Experience with cloud-based data platforms such as AWS, GCP or Azure
- Ability to work with unstructured data sources such as social media or web analytics
- Familiarity with data governance and data quality frameworks
- Ability to create visualisations/dashboards to communicate insights and findings
OKRs and KPIs
Objective 1:
- Automate at least 50% of data collection, processing, and analysis workflows
- Improve data analysis efficiency and accuracy
- Reduce data collection and analysis errors by at least 20%
- Increase the speed of data analysis by at least 30%
Objective 2:
- Conduct user research to identify key needs and pain points
- Increase understanding of user needs through data analysis
- Analyze user data to uncover trends and insights related to user needs
- Develop at least two user personas based on data analysis
Objective 3:
- Identify at least three business opportunities through data analysis
- Improve business performance through data-driven decision-making
- Provide recommendations to improve business performance based on data analysis
- Communicate data-driven insights and recommendations to non-technical stakeholders at least once a month
Requirements
Hard Skills
- SQL : Proficiency in writing queries to manipulate and analyse data stored in relational databases
- Python or R Knowledge of programming languages to perform statistical analysis
- Data manipulation and automation tasks
- Data Visualisation: Experience with tools such as Tableau, PowerBI or Looker
- Statistics : Understanding statistical concepts and methods such as hypothesis testing/regression analysis
- Data Cleaning: Ability to clean and transform data to ensure accuracy and consistency
Soft Skills
- Communication : Ability to effectively communicate findings and insights to non-technical stakeholders
- Collaboration : Capacity to work effectively with cross-functional teams to identify business opportunities
- Time Management : Ability to prioritise tasks and meet deadlines
- Attention to Detail : Being meticulous and accurate in data collection, analysis, and interpretation
- Problem-solving : Capability to identify problems and develop creative solutions