Data Analyst - Python

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.