01Overview
Role OverviewWe are seeking an experienced Data Analytics & Data Modelling Professional to join our growing Financial Services Technology team. The successful candidate will work on high-impact engagements for major banking and financial services clients, leveraging advanced analytical tools and techniques to extract, transform, query, and analyze large-scale datasets. They will play a pivotal role in delivering data-driven solutions that support risk management, regulatory compliance, customer analytics, product performance, and strategic planning for our clients.---Key ResponsibilitiesData Analytics & Insights Analyze large and complex datasets related to financial and banking products including retail lending, credit cards, mortgages, deposits, treasury, trade finance, and wealth management Develop comprehensive analytical reports, dashboards, and presentations to communicate findings and recommendations to senior client stakeholders and leadership teams Perform exploratory data analysis (EDA), trend analysis, segmentation analysis, and predictive modelling to support business decision-making Identify data patterns, anomalies, and correlations within transactional, behavioral, and financial dataData Modelling & Architecture Design, develop, and optimize logical and physical data models (conceptual, dimensional, and relational) for financial services data environments Build and maintain robust data models that support regulatory reporting, risk analytics, customer 360 views, and product profitability analysis Ensure data models are scalable, well-documented, and aligned with industry standards.Database Querying & Management (MySQL) Write complex, optimized SQL queries in MySQL to extract, manipulate, and transform large volumes of structured data from relational databases Develop and maintain stored procedures, views, functions, and triggers for data processing and automation Perform database performance tuning, query optimization, and indexing strategies to enhance data retrieval efficiency Manage data extraction pipelines and ensure data integrity, accuracy, and consistency across multiple data sourcesStatistical Analysis (SPSS) Utilize IBM SPSS Statistics for advanced statistical analysis, hypothesis testing, regression modelling, factor analysis, cluster analysis, and other multivariate techniques Develop predictive and descriptive models using SPSS for credit scoring, customer churn prediction, risk assessment, fraud detection, and product propensity modelling Automate recurring analytical workflows and reporting using SPSS syntax and scripting capabilities Validate model outputs and ensure statistical rigor and compliance with internal and regulatory standardsClient Engagement & Advisory Work directly with banking and financial services clients to understand business requirements and translate them into analytical frameworks and data solutions Present findings, insights, and strategic recommendations to C-suite executives, product heads, and risk officers Support business development activities including proposal writing, solution design, and effort estimation Mentor and guide junior team members, fostering a culture of analytical excellence and continuous learning---Required QualificationsEducation Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, Economics, Finance, or a related quantitative discipline Master's degree (MBA, M.Sc., M.Tech) in a relevant field is highly preferredExperience Minimum 25 years of professional experience in data analytics, data modelling, and quantitative analysis Minimum 23 years of direct experience working with financial services / banking clients (either in-house or in a consulting capacity) Proven track record of working on projects related to banking products such as loans, credit cards, deposits, payments, risk, compliance, or regulatory reportingTechnical Skills (Mandatory) MySQL: Expert-level proficiency in writing complex SQL queries, stored procedures, data manipulation, performance tuning, and database management IBM SPSS Statistics: Strong hands-on experience in statistical modelling, data analysis, syntax programming, and report generation using SPSS Data Modelling: Expertise in relational and dimensional data modelling techniques (Star Schema, Snowflake Schema, ER Modelling) using tools such as ERwin, PowerDesigner, or equivalent Large Dataset Management: Demonstrated ability to work with high-volume datasets (millions to billions of records) with efficiency and accuracyDomain Knowledge (Expected) Strong understanding of banking and financial products retail banking, corporate banking, credit risk, market risk, regulatory reporting, and compliance frameworks Understanding of financial data taxonomies, chart of accounts, general ledger structures, and customer data hierarchiesSoft Skills Excellent analytical thinking and problem-solving abilities Strong verbal and written communication skills with the ability to present complex
