Data Scientist

Job Purpose
The Digital Experience Analytics team is looking for skilled and motivated data scientists specializing in Generative Al and Machine Learning.
The Data Scientist will design, develop and deploy advanced Al models to drive digital transformation, enhance customer experience, optimize operations and mitigate risks. This role requires a sound understanding of Al/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:
1. Generative Al Model Development: Develop and fine-tune Gen Al 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 Al solutions into production environments, planning for scalability, reliability and regulatory compliance.
3. Research & Innovation: Stay updated on emerging Al/ML technologies and application in BFSI sector, including Explainable Al & Ethical Al.
4. Ensure Al 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 5 - 10 years' proven experience as a Data Scientist
• Bachelor's or Master's degree in Computer Science, Engineering, Data Science or similar Quantitative field is required.
• Certifications in Al/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 APls (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 stakeholders

Work arrangement
No