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Step into a role where your analytical mindset and digital fluency fuel progress in financial operations. Shape smarter data practices that support regulatory standards and elevate client trust. Lead by example, inspiring a culture of accountability and proactive risk management. Collaborate with forward-thinking professionals who value innovation and continuous growth. Make a lasting impact by driving best-in-class service and operational integrity.

MBA, master’s degree in economics, Statistics, Computer Science Or related fields 0-30 months of experience in analytics, big data workstreams. Ability to work effectively in a team environment Ability to drive project deliverables to achieve business results Strong communication and interpersonal skills Innovative problem solver with ability to learn quickly and work independently with complex, unstructured initiatives Ability to Integrate with Cross-Functional Business Partners Worldwide SAS, R, Python, Hive, Spark, SQL Unsupervised and supervised techniques -: active learning, transfer learning, neural models, Decision trees, reinforcement learning, graphical models, Gaussian processes, Bayesian models, Map Reduce techniques, attribute engineering

Job Description / Responsibilities: Collect, clean, transform, and analyse data from multiple sources. Develop interactive dashboards and reports using Power BI. Create and maintain Power BI data models and DAX measures. Automate repetitive reporting processes wherever possible. Perform data validation to ensure data accuracy and consistency. Collaborate with cross-functional teams to deliver analytics solutions.

To support the bank's decision-making processes by providing timely, accurate, and insightful information through designing, developing, and maintaining management reports, compelling visualisations and dashboards that effectively communicate key performance indicators (KPIs), data insights and trends across various business units.

Roles and Responsibilities :- Write SQL queries to pull and analyze payments data (transactions, success/failure rates, settlements). Monitor key payments metrics and flag anomalies or drop-offs proactively. Build and maintain simple dashboards/reports for ongoing visibility. Turn data into clear insights for the team - not just raw numbers. Support ad-hoc data requests from Payments, Finance, and Product teams.

Design and develop scalable data pipelines using Python and SQL. Analyze complex data sets to identify trends and patterns. Develop and maintain databases and data systems for business intelligence. Collaborate with cross-functional teams to integrate data into various applications. Develop predictive models using Gen AI and machine learning algorithms. Ensure data quality and integrity by implementing data validation and testing procedures.

Responsibilities Analyzes complex business problems using data from internal and external sources. Provides actionable insight to decision-makers to influence strategy and performance. Identifies and interprets trends and patterns in datasets to attribute key business drivers. Analyzes and defines metrics that tie back to business performance and initiatives. Will be a proponent of test/learn culture by enabling and supporting experimentation. Generates forecasts, recommendations, and strategic/tactical plans to drive actions. Creates specifications and generates reports and analysis mapping to business needs. May provide consultation and lead cross-functional teams to address business issues. Directly produces datasets and reports for analysis using databases and reporting tools.

Basic Qualifications - Experience with SQL or ETL - Experience defining requirements and using data and metrics to draw business insights - 1+ years of Excel or Tableau (data manipulation, macros, charts and pivot tables) experience - 1+ years of data analysis work and leveraging analytics to make decisions experience - Bachelor's degree in relevant field