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Data Analyst
interactive investor. Extract and analyse data from data lakes and relevant sources to provide actionable insights for business decisions and strategy formulation .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data extraction, analysis, and reporting using SQL, Python, and Power BI, while ensuring data accuracy and compliance with data protection laws. Capable of developing actionable insights and KPIs to drive business strategy and product improvements.
Highest-signal resume keywords
SQL ProficiencyData Visualization ToolsStatistical ModelingAI and Machine Learning PlatformsStakeholder Management
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data AnalysisStatistical TechniquesPredictive ModelingData ModelingSegmentation AnalysisTime Series AnalysisA/B TestingFunnel OptimizationConversion Rate OptimizationKPI Development
Soft Skills
Effective CommunicationProblem-SolvingCritical ThinkingRelationship BuildingAttention to Detail
Tools & Technologies
Power BIGoogle AnalyticsSnowflakeUsabillaOptimizelyContentSquareHotjarGoogle Marketing CloudJiraConfluence
Industry Keywords
Investment IndustryFinancial MarketsDigital ProductCommercial ContextData Protection Compliance
Tech Stack
Tools & technologiesCloudPythonSQL
About the role
Key responsibilities & impact- Extract and analyse data from data lakes and relevant sources to provide actionable insights for business decisions and strategy formulation
- Develop, maintain, and automate BI and MI reports, ensuring data accuracy and relevance
- Automate reporting capabilities using SQL, Python, Power BI, and other tools
- Partner with Product, Commercial, Technology, Customer Services, and Operations stakeholders to support data needs and product/service improvements
- Develop and track KPIs and data insights across the company
- Use SQL, Snowflake, Power BI, Usabilla, Google Analytics, Optimizely, ContentSquare, and Hotjar for analysis and reporting
- Apply statistical modelling, segmentation analysis, time series analysis, and predictive techniques to analyse customer behaviour and assess business impacts
- Leverage existing AI and machine learning platforms as a power user
- Conduct cross-channel analysis across all channels and systems
- Mentor and support team members in analytical best practices
- Ensure compliance with data protection laws and company policies
- Integrate data-driven insights into business processes and strategic initiatives
- Stay current with analytics tools, techniques, trends, and best practices
- Monitor and report on relevant KPIs
- Implement innovative solutions and continuous process improvements
- Participate in problem-solving sessions, knowledge sharing, and collaborative projects
- Report to the Data Analytics and Insights Manager
Requirements
What you’ll need- Strong background in analytics, ideally within a commercial or digital product/service context
- Proficiency in SQL, data visualisation tools (e.g., Streamlit/Python, Power BI, Data Studio/Looker, GA4 Reports), and dashboard/report creation
- Experience with Google Marketing Cloud, inc. Google Tag Manager, Google Analytics, Google Search Console, etc
- Knowledge of statistical concepts, techniques, and methodologies, and experience with data modelling and architecture
- Experience of data science techniques and methodologies, for example statistical modeling, segmentation analysis, time series analysis, predictive modeling approaches, or other data modelling
- Experience using AI and machine learning platforms and tools as a power user
- Effective communication and presentation skills, able to transform complex data into clear insights
- Strong stakeholder management skills
- Proactive, personable, and able to build relationships across teams
- Excellent problem-solving, critical thinking, and attention to detail
- Ability to manage multiple priorities and deliver results within deadlines
- Understanding of KPIs and success measures
- Experience in data projects
- Experience in the investment industry or a strong interest in financial markets (desirable)
- Interest in investing, with knowledge of investment products and market trends (desirable)
- Proficiency in Python, or other languages, for data analysis (desirable)
- Experience with A/B testing, funnel optimisation, and conversion rate optimisation techniques (desirable)
- Familiarity with machine learning techniques and their application in predictive modelling (desirable)
- Familiarity with Jira/Confluence or similar project management tools (desirable)
Benefits
Comp & perks- Group Personal Pension Plan – 8% employer contribution and 4% employee contribution
- Life Assurance and Group Income Protection
- Private Medical Insurance – Provided by Bupa
- 25 Days Annual Leave, plus bank holidays
- Staff Discounts on our investment products
- Personal & Well-being Fund – Supporting your physical and mental wellness
- Retail Discounts – Savings at a wide range of high street and online retailers
- Voluntary Flexible Benefits – Tailor your benefits to suit your lifestyle