Urgent Hiring - Data Analytics & Data Modelling Professional

Role Overview

We 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.

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Key Responsibilities

Data 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 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

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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 (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 reporting

Technical 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 accuracy

Domain 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 hierarchies

Soft Skills

Excellent analytical thinking and problem-solving abilities

Strong verbal and written communication skills with the ability to present complex technical concepts to non-technical audiences

Ability to work independently and collaboratively in a fast-paced, client-facing consulting environment

Strong project management and organizational skills with the ability to manage multiple workstreams simultaneously

Leadership qualities with experience in mentoring and guiding junior analysts

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Preferred / Nice-to-Have Qualifications

Experience with additional analytics/BI tools such as Python, R, SAS, Tableau, Power BI, or Alteryx

Exposure to cloud-based data platforms (AWS RDS, Google BigQuery, Azure SQL Database)

Knowledge of ETL processes and data integration frameworks

Professional certifications such as:

Certified Analytics Professional (CAP)

IBM SPSS Certified Specialist

MySQL Database Administrator Certification

FRM (Financial Risk Manager) or CFA (any level)

PMP or Agile/Scrum certifications

Experience with data governance data quality frameworks, and master data management (MDM)