Business Analyst
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Data-driven professional with 5+ years of experience in project management, business analysis, and recruitment. Currently pursuing a Master's in Business Analytics, leveraging expertise in R, Python, SQL, data visualisation, and machine learning to deliver data-driven insights. Skilled in eliciting requirements, managing projects using agile methodologies, and streamlining processes.
Background includes coordinating multiple stakeholders, optimising recruitment operations, and conducting user acceptance testing. Excellent problem-solver and communicator adept at building cross-functional relationships. Seeking to apply analytical skills and passion for continuous improvement to drive smarter decisions and business success.
Results-driven and detail-oriented professional with a strong background in project coordination, recruitment, and current postgraduate studies in Business Analytics from Queen's University Belfast. Skilled in programming languages including R, SQL, and Python, with experience utilising visualisation tools such as Knime and Tableau. Proficient in project management tools like Jira and Slack, as well as design tools like Adobe XD.
Possesses expertise in eliciting, analysing, and documenting business requirements, and has a track record of successfully managing multiple projects and stakeholders. Adept at conducting user acceptance testing, streamlining recruitment processes, and facilitating agile methodologies. Demonstrates strong interpersonal skills and acts as a bridge between clients, hiring managers, and candidates.
Highly organised with excellent communication and problem-solving abilities. Committed to delivering high-quality results and driving business success through data-driven insights, strategic decision-making, and talent acquisition.
Statistics for Business: Covers probability, descriptive and inferential statistics using R programming language.
Data Management: Focuses on managing data, data extraction using SQL, data quality, data warehousing, and big data solutions.
HR Analytics: Explores practical use of data in HRM, including monitoring and evaluating employee activity, predicting future performance, and employee attrition.
Artificial Intelligence in Business and Society: Examines the strategic implications of AI innovations, economic and societal consequences, changes in the nature of work, and ethical use of data.
Advanced Analytics and Machine Learning: Builds on statistical skills with machine learning algorithms, ethics considerations, and model performance evaluation.
Data Mining: Focuses on data mining using Python, analyzing unstructured data, and ethical considerations.
Data Driven Decision Making: Explores data visualization, prescriptive analytics, managerial and organizational factors in data-driven decision making.
Marketing Analytics: Applies analytics techniques to marketing problems, including customer segmentation, pricing, and customer retention.
