Data Analyst

Job Description

We're Hiring: Data Analyst – Fintech | Fraud Detection | Advanced Analytics About the Role:We are looking for a highly technical and experienced Data Analyst to join our team. This role focuses on building scalable data pipelines, designing advanced analytics frameworks, and developing detection mechanisms to prevent fraudulent activity. You will operate at the intersection of big data, security, and machine learning—closely collaborating with developers, leadership, and business stakeholders. Key Responsibilities:Design, implement, and maintain robust data pipelines to support tracking, fraud detection, and KPI measurementTransform large volumes of unstructured data into clean, structured databasesWrite and optimize complex SQL queries and data models to extract meaningful insightsAnalyze user behavior to detect fraud patterns and convert findings into production-ready rule logicBuild and deploy static rules and data features for real-time fraud mitigationParticipate in on-call rotations to monitor fraud events and system anomaliesDevelop self-service dashboards and reporting tools using Tableau or similar BI platformsAutomate monitoring systems using Excel, SQL, Python, or AWS tools for early fraud detectionPresent technical findings clearly to both business and engineering teams Tech Stack & Tools:Languages & Tools: Advanced Excel, SQL, Python (pandas, NumPy), MS Office, G-SuiteBI & Visualization: Tableau, Amazon QuickSight, Power BIData Infrastructure: AWS (Redshift, Athena, S3)Version Control & Deployment: Git, GitHub, CI/CDData Modeling: Experience in building reusable models and attributes for fraud detection A Day in the Life:Investigate suspicious patterns using multiple data sourcesCreate daily progress and revenue tracking reportsBuild scalable dashboards for business transparencyCollaborate with engineering teams to implement rule logic and signalsRefine existing detection rules and validate new hypotheses using statistical methodsEnhance anomaly detection systems and refine fraud KPIs Basic Qualifications:Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, or related fieldMinimum 4 years of experience in a technical data analyst, risk analyst, or data engineering roleStrong SQL and Python skills for handling large-scale datasetsExperience with BI tools such as Tableau, Power BI, or QuickSightUnderstanding of working with sensitive data in secure environments Preferred Qualifications:3+ years in financial services, NBFCs, banks, or fintech companiesFamiliarity with machine learning concepts and using model outputsPrior experience building detection systems in high-scale production setupsRelevant certifications in data analytics, risk, or AWS tools