HSBC Data Scientist Recruitment 2026: Apply Online
Recruitment of Data Scientist (Job ID: 52392) in Kolkata & Bangalore
Organization: HSBC | Post: Data Scientist | Job ID: 52392 | Work Mode: Hybrid | Location: Kolkata & Bangalore | Application Fee: Nil (Free for All) | Eligibility: Degree in CS, Data Science, Statistics, AI/ML or Related Field | Experience: GenAI, LLMs, Machine Learning, Python |
Latest Update
HSBC is officially hiring for the position of Data Scientist (Job ID: 52392) for its technology centers in Kolkata, West Bengal and Bangalore, Karnataka. This is a full-time hybrid career opportunity for professionals possessing specialized expertise in Data Science, Artificial Intelligence, Machine Learning, Generative AI, Large Language Models (LLMs), Python programming, and scalable Data Engineering. Interested candidates can review the detailed requirements and apply online directly through the official HSBC Careers portal.
- Overview
- Important Dates
- Required Technical Skills
- GenAI & Large Language Model Competencies
- Classical Machine Learning Expertise
- MLOps & Data Engineering Skills
- Key Technologies & Frameworks
- Job Responsibilities & Operating Model
- Important Links
- How to Apply Online
- Important Links Table
- Frequently Asked Questions (FAQs)
Overview
| Particulars | Details |
|---|---|
| Company / Organization | HSBC Holdings plc |
| Post Name | Data Scientist |
| Job ID / Requisition ID | 52392 |
| Job Location | Kolkata, West Bengal & Bangalore, Karnataka, India |
| Work Style | Hybrid Worker |
| Employment Type | Full-Time |
| Job Category | Data Science / Artificial Intelligence / Machine Learning |
| Application Fee | Nil (Free for All Applicants) |
| Application Mode | Online |
| Official Careers Website | www.hsbc.com/careers |
Important Dates
| Event | Date |
|---|---|
| Job Posting Date | 13 August 2026 |
| Last Date to Apply Online | 14 August 2026 |
Required Technical Skills
- In-depth conceptual and practical understanding of Generative AI, transformer architectures, and Large Language Models (LLMs).
- Practical knowledge of prompt engineering patterns, context management, tokenisation, and function calling.
- Familiarity with LLM failure modes including hallucinations, grounding, and context window limits.
- Hands-on experience building Retrieval-Augmented Generation (RAG) architectures and multi-agent AI workflows.
- Proficiency with vector embeddings, semantic search, vector databases, and re-ranking algorithms.
- Strong foundation in classical supervised and unsupervised Machine Learning algorithms.
- Advanced Python programming with clean coding practices and API development experience.
- Robust SQL and data engineering fundamentals for querying and processing large-scale datasets.
GenAI & Large Language Model Competencies
| Area | Core Focus & Concepts |
|---|---|
| Architecture & Design | Transformer Models, Tokenisation, Attention Mechanisms, Foundation Models |
| Application Frameworks | RAG Architectures, Agentic Workflows, Function Calling, Prompt Orchestration |
| Vector Retrieval | Vector Databases, Dense Embeddings, Re-Ranking, Semantic Indexing |
| Evaluation & Safety | Factuality, Groundedness, Hallucination Detection, Toxicity & Bias Evaluation |
Classical Machine Learning Expertise
- Supervised & Unsupervised Learning: Decision Trees, Ensemble Methods (Random Forest, XGBoost), Clustering, and Dimensionality Reduction.
- Statistical Modeling: Hypothesis testing, feature selection, feature engineering, and bias-variance trade-off optimization.
- Evaluation Metrics: Precision, Recall, F1-Score, ROC-AUC, Precision-Recall Curves, and offline vs. online testing methodologies.
MLOps & Data Engineering Skills
- Reproducible Pipelines: Building automated CI/CD workflows for machine learning models and experiment tracking.
- Model Governance: Model registry, data quality validation, drift detection, and safe canary rollout strategies.
- Big Data & ETL: Experience with Apache Spark, Databricks, distributed data modeling, and training dataset pipeline development.
Key Technologies & Frameworks
- Languages: Python, SQL
- ML & Deep Learning: PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers
- GenAI & Search: LangChain, LlamaIndex, Vector Databases (Pinecone, Milvus, Chroma, Weaviate)
- Data Platforms: Apache Spark, Databricks, Cloud Data Warehouses
Job Responsibilities & Operating Model
- Provide advanced Data Science and Data Management capabilities to Global Businesses and Functions.
- Design, train, test, and deploy enterprise-grade AI, classical ML, and LLM applications into production environments.
- Lead transaction screening analytics and tuning functions aligned with group sanctions screening and compliance policies.
- Develop technical solutions adhering to global data management and security regulations.
- Establish robust MLOps practices, maintain Standard Operating Procedures (SOPs), and improve hit rates across business lines.
Important Links
How to Apply Online
Step 1: Visit the official job requisition page: HSBC Data Scientist Application Link.
Step 2: Review the comprehensive job details, key capabilities, and eligibility criteria.
Step 3: Click on the "Apply Now" button and create or log in to your HSBC candidate profile.
Step 4: Upload your updated Resume / CV showcasing your experience in Data Science, GenAI, Python, and ML systems.
Step 5: Fill in personal details, educational background, professional experience, and preferred location (Kolkata or Bangalore).
Step 6: Review your application information carefully and submit the form.
Important Links Table
| Descriptions | Link |
|---|---|
| Direct Online Application Link | Click Here to Apply |
| HSBC Careers Portal | Visit HSBC Careers |
| HSBC Official Website | www.hsbc.com |
Frequently Asked Questions (FAQs)
Q1. What is the post name and Job ID in HSBC Recruitment 2026?
Ans: The post name is Data Scientist under Job ID 52392.
Q2. Where are the job locations for this HSBC role?
Ans: The positions are available in Kolkata (West Bengal) and Bangalore (Karnataka), India.
Q3. What is the work model for the Data Scientist position?
Ans: The role follows a Hybrid Worker model offering flexibility between office and remote work.
Q4. Which technical skills are essential for this role?
Ans: Strong expertise in Python, SQL, Generative AI, Large Language Models (LLMs), RAG architectures, Classical Machine Learning, MLOps, and Data Engineering.
Q5. Is there any application fee for HSBC job applications?
Ans: No, applying for career opportunities at HSBC is 100% free of cost.
Q6. How can I apply for the HSBC Data Scientist role?
Ans: Eligible candidates can apply directly through the official HSBC Careers link provided in the Important Links section above.