Data Analyst

Key Responsibilities

1. Business Problem Solving & Analytics

• Partner closely with cross-functional teams across Business, Product, Technology, Operations, Risk, and other functions to identify and define high-impact business problems.
• Translate ambiguous business requirements into structured analytical problem statements and actionable hypotheses.
• Independently identify relevant data sources, define analytical logic, and build robust solutions.
• Generate actionable insights that influence business strategy and decision-making.

2. Data & Technical Expertise

• Work extensively with large and complex datasets to extract, process, and analyse information.
• Build efficient and scalable data solutions using SQL and Python.
• Develop advanced analytical models, automation frameworks, and reusable datasets.
• Ensure accuracy, robustness, and scalability of analytical solutions.

3. Dashboarding & Data Storytelling

• Build intuitive and insightful dashboards using Tableau or similar visualization tools.
• Go beyond reporting by identifying the underlying business drivers and translating data into actionable insights.
• Develop self-service analytical solutions that enable stakeholders to independently access relevant information.

4. AI & Advanced Analytics

• Identify opportunities to leverage AI and Generative AI to improve analytical workflows, business decision-making, and operational efficiency.
• Build and experiment with AI-enabled solutions, including applications leveraging LLMs, automation, and intelligent decision systems.
• Drive the adoption of AI within analytics to reduce manual effort and improve the speed and quality of insights.
• Stay updated with emerging AI technologies and translate relevant capabilities into practical business use cases.

5. Cross-functional Collaboration

• Work directly with senior stakeholders to understand business challenges and independently drive analytical initiatives.
• Collaborate with Data Engineering, Technology, Product, and Business teams to ensure the availability and usability of relevant data.
• Act as a bridge between business and technical teams by converting business problems into clear analytical requirements.

6. Ownership & Execution

• Take complete ownership of analytical initiatives from problem definition to implementation and impact measurement.
• Proactively identify opportunities and problems rather than waiting for detailed instructions.
• Operate effectively in an ambiguous and fast-paced environment.
• Challenge existing approaches and continuously look for opportunities to improve processes, tools, and decision-making.

What We Are Looking For

The ideal candidate is:

• High on ownership, taking responsibility for outcomes rather than just completing assigned tasks.
• Hands-on technically, with the ability to independently work with SQL, Python, Tableau, and large datasets.
• AI-native, with practical experience experimenting with and building AI-enabled solutions.
• Business-oriented, with the ability to engage confidently with senior stakeholders and influence decisions.
• Collaborative, with a strong ability to work across functions and bring different teams together to solve problems.
• Experience in fintech is preferable.