Data Analyst

Job Description

Key Responsibilities

1. Business Problem Solving & Analytics

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

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

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

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

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

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

The ideal candidate is:

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