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Data Analyst
Hybrid- St Julians, Saint Julian's, Malta
Technology
Job description
Who we are:
eCabs Technologies is in a relentless drive to optimise its robust, multi-channel ride-hailing platform, currently deployed in three countries, and with ambitious plans for future growth in multiple regions. In line with our aspirations to be a key player in the international mobility industry, we are currently on the lookout for a Data Analyst.
Who you are:
As a Data Analyst, you will play a crucial role in analysing and interpreting complex data sets to drive strategic decision-making within the company. You will collaborate closely with cross-functional teams to extract actionable insights and contribute to the development of innovative solutions.
What you’ll do:
- Collect, analyze, and interpret large datasets to identify trends, patterns, and insights.
- Develop and maintain data systems and databases; this includes fixing coding errors and other data-related problems.
- Generate reports and dashboards to support business decision-making.
- Work closely with the management team to prioritize business and information needs.
- Use statistical tools to interpret data sets, paying particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics efforts.
- Demonstrate a logical and analytical approach to identifying and resolving complex issues.
- Provide ongoing reports and make recommendations for optimizing business performance.
- Perform data validation and quality assurance checks.
- Collaborate with different departments to understand their data needs and provide tailored solutions.
Job requirements
What you'll bring:
- Bachelor of Arts degree and 3+ years of experience in data analysis or a similar field.
- Proficiency in data analysis tools and software (e.g., SQL, Excel, R, Python).
- Experience with data visualization tools (e.g., Tableau, Power BI).
- Strong analytical and problem-solving skills.
- Excellent communication skills, both written and verbal, with the ability to present complex data findings in a clear and concise manner.
- Attention to detail and a commitment to accuracy and integrity in data analysis.
- Ability to work collaboratively with cross-functional teams and manage multiple projects simultaneously.
- Familiarity with data warehousing concepts and tools is a plus.
- Knowledge of machine learning algorithms and statistical methods is a plus.
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