The data analyst role is embedded in a business domain and reports into a leader within the domain. Business domains include but are not limited to, Commercial, Finance, Compliance, Marketing, Sales, Customer Servicing, Human Capital and Product.
In this role, the data analyst will collaborate cross functionally to understand business problems and then build data driven solutions to solve them, having the opportunity to work across full spectrum of descriptive, diagnostic, predictive and prescriptive analytics. Data analysts work in close alignment with the Business Intelligence team, benefiting from their data architecture, tooling, and technical expertise.
Duties and Responsibilities (Include but is not limited to):
- Work closely with stakeholders across all levels and business areas to elicit data & analysis requirements
- Translate requirements into reporting or data analysis specifications employing critical thinking to ensure alignment with the actual business need.
- Be the translator between Business, Product, and the Data teams on data needs
- Interview subject matter experts and shadow workflows to build an understanding of our data collection and logging processes. In time, become an expert in our data.
- Specify, gather, clean, combine and aggregate data from disparate sources for data analysis and reporting needs
- Profile and validate all data intended for use in reporting or analysis to ensure high data quality (accuracy, completeness, missing/invalid data correction, timeliness)
- Perform data analysis to (not exhaustive):
- Extract key insights and observations to influence/support business decisions and actions
- Identify the core drivers/levers and segments that influence the movement of key metrics/KPIs
- Identify gaps in existing business processes and product offerings and formulate recommendations to improve them
- Measure the effectiveness of product launches and new business initiatives
- Design, build, and maintain reports to track and communicate KPIs and results from data analysis activities
- Build data visualizations to improve access and visibility into the content from all key reports and our data in general
- Share insights and analysis results in written form and in business presentations
- Train and support user community in the use of reports, BI tools, and the interpretation of analysis results
- Collect and apply feedback from business presentations, user training and peer review to continuously improve reporting and analysis solutions
- Proactively communicate the status (including blockers, risks, issues) and roadmap of the work assigned to you, with all affected stakeholders
- Cultivate relationships and collaborate cross-functionally to shape, support, and execute on business and product goals
- Help define and improve upon our analytics standards through participation within the community of practice, conducting peer reviews and contribution to internal documentation
- Identify data quality issues, their corresponding root cause and collaborate with business, product, and data teams to drive improvements in data hygiene
- Continuously upskill and stay abreast of new developments in Data Analysis & BI tools, methodologies, and applications
- Grade 12 or equivalent (Essential)
- Tertiary qualification in a quantitative field (includes but not limited to – Mathematics, Statistics, Engineering, Computer Science, Actuarial Science, Economics, Finance, Business Analytics)
- 4+ years working experience within Data Analytics or business intelligence (Essential)
- Strong verbal and written communication skills in English and understand how to share insights and analytical results to both technical and non-technical audiences.
- Knows how to work with stakeholders to gather Data & Analysis requirements and communicate findings
- Strong report/dashboard development and data visualization skills with modern BI tools (e.g., Power BI, Tableau, Qlik)
- Advanced SQL skills
- Advanced Excel skills
- R or Python programming for data analysis (desirable)
- Experience cleaning, assimilating, manipulating, and aggregating large data sets using SQL, R or Python or similar tools
- Knowledge of data analysis techniques, such as time series analysis, scenario analysis, clustering & segmentation, regression, decision trees, forecasting, and interpretation & creation of probability distributions (proficiency in a few of these will suffice)
- Analytical and problem-solving skills
- Execution-oriented, and able to complete tasks independently