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.

---

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 2–5 years of professional experience in data analytics, data modelling, and quantitative analysis

· Minimum 2–3 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)