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.

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

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 skilled 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

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)

📌 Urgent Hiring - Data Analytics ( Senior Consultant) (Mumbai)
🏢 PwC India
📍 Mumbai