Data Analyst

Data Analyst Assistant Manager - Program Analytics Team | Full-Time | 1–2 Years Experience About the Role We are looking for a detail-oriented and analytically driven Data Analyst to join our growing analytics team. You will work with structured and unstructured datasets to generate insights, build models, and support data-driven decision-making across the organisation. Key Responsibilities Analyse large datasets using Python to surface actionable insights Build, evaluate, and maintain machine learning models for classification, regression, and NLP tasks Integrate and work with generative AI, including local and cloud-hosted LLMs, to augment analytical workflows and automate text-heavy tasks Design and maintain interactive dashboards and reports in Power BI Write and optimise SQL queries for data extraction, transformation, and reporting Prepare executive-ready presentations and summaries in PowerPoint; maintain structured data in Excel Apply statistical methods (e.g. hypothesis testing, regression analysis, distribution modelling) to validate findings Collaborate with cross-functional stakeholders to translate business questions into analytical frameworks Required Skills & Qualifications Technical Skills Python: pandas, scikit-learn, seaborn, NLTK Data visualisation: Power BI (report building, DAX, data modelling) Databases: SQL (query writing, joins, aggregations, window functions) Office tools: Microsoft Excel (PivotTables and Power Query) and PowerPoint Statistical acumen: hypothesis testing, A/B testing, regression, probability distributions, significance testing Education Bachelor’s or master’s degree in Statistics, Mathematics, Data Science, Analytics, Computer Science, Engineering, or a related quantitative field Formal education requirements may be waived for candidates who demonstrate equivalent competence through work experience and a strong portfolio Experience 1–2 years of hands-on work experience in a data analyst, business analyst, or equivalent role Demonstrated experience working with real-world datasets and delivering analytical outputs Good to Have Familiarity with NLP pipelines and text analytics Experience with big data processing using PySpark Linux CLI proficiency: navigating file systems, shell scripting, running jobs on remote servers ML deployment exposure: serving models via FastAPI and building lightweight interfaces using Streamlit or Gradio Knowledge of data warehousing concepts or cloud platforms (Azure, GCP, AWS)