As an experienced Data Analytics & Data Modelling Professional joining the Financial Services Technology team, your role will involve working on high-impact engagements for major banking and financial services clients. You will leverage advanced analytical tools and techniques to extract, transform, query, and analyze large-scale datasets to deliver data-driven solutions supporting risk management, regulatory compliance, customer analytics, product performance, and strategic planning for clients. - **Key Responsibilities:**
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 data. - **Data 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 sources. - **Statistical 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 standards. - **Client 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 Qualifications:**
**Education:**
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 preferred. - **Experience:**
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. - **Technical Skills (Mandatory):**
Expert-level proficiency in MySQL for writing complex SQL queries. - Strong hands-on experience in statistical modelling using IBM SPSS Statistics. - Expertise in relational and dimensional data modelling techniques. - Demonstrated ability to work with high-volume datasets efficiently and accurately. - **Domain Knowledge (Expected):**
Strong understanding of banking and financial products. - Understanding of financial data taxonomies, chart of accounts, general ledger structures, and customer data hierarchies. - **Soft Skills:**
Excellent analytical thinking and problem-solving abilities. - Strong verbal and written communication skills. - Ability to work independently and collaboratively in a fast-paced, client-facing consulting environment. - Strong project management and organizational skills. - Leadership qualities with experience in mentoring and guiding junior analysts. The job description does not provide any additional details about the company. As an experienced Data Analytics & Data Modelling Professional joining the Financial Services Technology team, your role will involve working on high-impact eng
