Junior Data Scientist | Sundaram Housing Finance Careers | Chennai HO

About the Company: Six Decades of Financial Trust

Sundaram Housing Finance is a subsidiary of one of India’s most resilient and respected financial conglomerates. Backed by a phenomenal six-decade heritage, the overarching group commands a robust pan-India presence across automotive financing, retail lending, general insurance, wealth management, and mortgage systems.

Built on a foundation of operational transparency, consumer empathy, and prudent risk management, Sundaram represents absolute trust in the Indian financial landscape. By joining our data intelligence division, you enter an ecosystem that leverages modern quantitative frameworks to simplify homeownership finance while maintaining the timeless values of security, corporate governance, and financial excellence.

About the Role: Junior Data Scientist

Are you a data enthusiast who loves building predictive models that solve real-world financial challenges? Sundaram Housing Finance is seeking a high-calibre, analytically driven Junior Data Scientist to join our elite analytics engine at our Chennai Head Office (HO).

Reporting directly to the Head of Analytics & Data Science, you will transition past basic data querying to build, deploy, and maintain production-grade analytical assets. This full-time, permanent position is tailored for professionals with 1 to 4 years of experience who possess a strong mathematical coding aptitude. You will spend your days extracting patterns from large-scale transactional datasets, engineering feature sets, and deploying statistical models to manage credit risks, forecast market trends, and optimise financial operations.

Key Responsibilities & Data Workflows

• Data Aggregation & Mining: Systematically collect, clean, and analyze high-volume structured and unstructured financial data pools across corporate repositories.

• Predictive Model Architecture: Develop, train, and optimise predictive algorithms and machine learning models—with a focus on handling feature selection and refinement for classification and regression problems.

• Production Deployment: Support the engineering pipeline by translating experimental data science models into clean, modular, and optimised code components that integrate seamlessly into live production environments.

• Data Pipeline Infrastructure: Collaborate with data engineering cohorts to design, support, and maintain stable, scalable data pipelines using cloud and big data frameworks.

• Stakeholder Synthesis: Translate complex mathematical conclusions into intuitive, actionable data stories, presenting metrics clearly to both technical engineers and non-technical business leaders.

• Cross-Functional Collaboration: Partner with risk, underwriting, and operations units to embed automated data insights directly into daily financial processes.

                        ┌────────────────────────────────────────┐
                        │    Data Intake: Structured/Unstructured│
                        └───────────────────┬────────────────────┘
                                            │
                  ┌─────────────────────────┴─────────────────────────┐
                  ▼                                                   ▼
┌──────────────────────────────────────┐            ┌──────────────────────────────────────┐
│       Statistical Modeling Layer     │            │      Production Engineering Layer     │
├──────────────────────────────────────┤            ├──────────────────────────────────────┤
│ • Classification & Regression Tasks  │ ──Code───> │ • Modular Python Execution Blocks    │
│ • Feature Engineering & Optimization │  Modules   │ • Big Data Pipelines (Spark/Hive)    │
│ • Power BI / Tableau Dashboards      │            │ • Scalable Cloud Deployments (AWS)   │
└──────────────────────────────────────┘            └──────────────────────────────────────┘

Candidate Prerequisites & Technical Matrix

We are looking for data professionals who combine mathematical rigor with stable software development practices.

Basic Qualifications & Skills:

• Experience Window: 1 to 4 years of stable, verified experience working within data science, predictive analytics, or a business intelligence framework.

• Educational Background: Graduate or Postgraduate degree in Data Science, Computer Science, Mathematics, or Engineering; or an MBA with a strong quantitative focus.

• Core Coding Toolkit: Exceptional hands-on proficiency in Python and advanced SQL database scripting.

• Statistical Foundation: Strong applied statistical background with a crystal-clear understanding of classification models, regression variants, and algorithmic parameters.

• Business Intelligence (BI): Direct exposure to designing, deploying, and maintaining executive tracking dashboards inside Power BI or Tableau.

• Domain Awareness: Foundational knowledge of financial services, lending lifecycle metrics, or banking operations is highly advantageous.

• Big Data & Cloud Exposure (Plus): Conceptual or practical familiarity with big data infrastructure components (Hadoop, Spark, Hive, Kafka) and cloud native environments (AWS).

Professional Framework & Corporate Value

• Reporting Matrix: Directly aligned under the Head of Analytics & Data Science.

• Operational Location: Full-time, Permanent placement at our corporate headquarters in Chennai, Tamil Nadu.

• Growth Environment: Access to large-scale, high-impact financial data tracks that offer deep professional exposure across multiple financial product portfolios.