About the role
Responsibilities:
- Data Processing and Analysis: Utilise Python (specifically libraries like pandas, NumPy, and SciPy) to extract, clean, manipulate, and analyse structured and unstructured data from multiple sources.
- Business Intelligence: Design, build, and maintain automated dashboards and reports using BI tools (e. g., Tableau and Power BI) to track key performance indicators (KPIs).
- Exploratory Data Analysis (EDA): Proactively investigate data anomalies, discover hidden patterns, and identify root causes behind business trends.
- Cross-Functional Collaboration: Partner directly with stakeholders and leadership to translate ambiguous business questions into measurable analytical projects.
- Data Pipeline Optimisation: Work alongside data engineering teams to improve data collection processes and ensure high data quality and integrity.
- Storytelling: Present complex technical findings in a clear, concise manner to non-technical audiences, ensuring insights are easily understood and actionable.
Requirements:
- Experience: 4 to 8 years of proven professional experience in data analysis, business intelligence, or a closely related field.
- Core Technical Skills: Advanced proficiency in Python for data manipulation and analysis.
- Database Querying: Strong hands-on experience with SQL for data extraction and database management.
- Visualisation: Solid experience with data visualisation libraries (like Matplotlib or Seaborn) and enterprise BI tools.
- Analytical Thinking: Exceptional problem-solving skills with a demonstrated ability to think logically and strategically.
- Communication: Excellent verbal and written communication skills, with a track record of successfully presenting data to leadership.
Nice-to-Haves:
- Familiarity with cloud platforms (AWS, GCP, or Azure).
- Experience with version control (Git) and collaborative environments like Jupyter Notebooks.
- Basic understanding of statistical modelling or machine learning concepts.