Skills required to master data analytics in Fintech

Domains

• Bank payments
• Card transactions
• Financial statements and forecasting
• Reconciliation
• Safeguarding
• Accounting
• Credit risk analysis

Methods of analysis

• Actionable KPIs
• Cohort analysis
• Financial metrics
• User funnels
• User interview best practices
• Customer journey mapping
• Lifetime value analysis
• Customer segmentation
• Conversion rate optimisation

Organisational skills

• Data quality best practices
• Sprints for data analysts
• Training and knowledge-sharing

Data modelling

• Relational data
• Naming conventions
• Reporting best practices

Statistics

• Descriptive statistics
• A/B tests
• Probability distributions
• Hypothesis testing
• Sample size
• Regressions
• Random forests
• Correlation and covariance
• Time series analysis
• Clustering

Data governance

• GDPR compliant data collection
• Working with personally identifiable data
• Security best practises

Tools

• Version control (Github)
• Data warehouses (BigQuery)
• ETL pipelines (Fivetran and Segment)
• Dashboarding (Looker and Metabase)
• Product analytics (Mixpanel, Amplitude)
• SQL
• Scripting (Python, R)
• Spreadsheets (Excel, Google Sheets)
• Testing frameworks (pytest, DBT)

Communication

• Presenting to an audience
• Storytelling through slides