Job Purpose:

The Digital Experience Analytics team is looking for skilled and motivated data scientists specializing in Generative AI and Machine Learning.

The Data Scientist will design, develop and deploy advanced AI models to drive digital transformation, enhance customer experience, optimize operations and mitigate risks. This role requires a sound understanding of AI/ML techniques and their application to challenges such as customer engagement and process automation.

The successful candidate will be an analytical problem solver, with a blend of technology understanding and business acumen. They should have hands-on experience with data analysis and model development using statistical techniques or machine learning methods. He/She should demonstrate a bias for action, have strong attention to detail, be vocally self-critical and capable of working in an ever-changing environment.

Job Responsibilities (JR):

1. Generative AI Model Development: Develop and fine-tune Gen AI models (eg GANs, VAEs or

transformer-based models) to implement process and system improvement opportunities.

2. Solution Deployment and Integration: Work with Engineering teams to deploy ML & Gen AI

solutions into production environments, planning for scalability, reliability and regulatory

compliance.

3. Research & Innovation: Stay updated on emerging AI/ML technologies and application in BFSI

sector, including Explainable AI & Ethical AI.

4. Ensure AI solutions comply with banking regulations, including data privacy and model

governance requirements.

5. Build tools for stress testing, scenario analysis and regulatory reporting.

6. Collaboration & Stakeholder Communication: Work closely with business units, technology

units and customer facing channels to understand banking-specific challenges, use-cases and

deliver effective solutions. Present technical solutions in a clear, actionable format to diverse

stakeholders.

Educational Qualifications:

Between 4 - 10 years proven experience as a Data Scientist
Bachelors or Masters degree in Computer Science, Engineering, Data Science or similar Quantitative field is required.
Certifications in AI/ML, Financial Analytics, Cloud Computing.

Key Skills:

Strong programming skills in Python, R, Pyspark, SQL
Experience with deep learning frameworks like TensorFlow, Pytorch or JAX
Familiarity with MLOps pipelines and tools for model lifecycle management
Expertise in working with cloud platforms (AWS, GCP, Azure) and financial-specific APIs (eg. UIDAI, NSDL, Bureaus etc)
Experimental mindset, quest for continuous learning
Knowledge of Banking Domain and Data is an advantage
Strong analytical and problem-solving abilities with attention to detail
Excellent communication skills to bridge the gap between technical teams and business

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