- Advise on the deployment of Generative AI solutions including selecting suitable models and best practices for integration in public sector banks.
- Guide AI/ML technology implementation for banking applications including data preparation model development and refinement for areas like Fraud & Risk Management.
- Lead the design development and deployment of Generative AI models for various banking use cases.
- Provide expertise on the GenAI tech stack including Large Language Models (LLMs) infrastructure and tools for successful deployment.
- Support the setup and integration of the GenAI tech stack including vendor integrations cloud architecture preprocessing prompt engineering and model finetuning.
- Stay updated on the latest advancements in GenAI technology and recommend solutions to enhance the bank s digital transformation.
Requirements
- Experience in AI/ML with at least 2 years focusing on Generative AI technologies.
- Proven track record in implementing AI solutions preferably in the banking or financial services industry.
- Expertise in AI/ML algorithms natural language processing (NLP) and Generative AI model deployment.
- Indepth understanding of the GenAI tech stack including LLMs cloud infrastructure and necessary tools for model development and integration.
- Strong problemsolving and analytical skills with experience in developing innovative AI solutions.
- Familiarity with AI/ML applications in banking such as fraud detection and risk management.
- Excellent communication skills to collaborate with teams and present findings to senior leadership.
- Experience in the banking or financial services industry.
- Familiarity with cloud platforms (e.g. AWS Azure GCP) and vendor integrations for AI/ML solutions.
- Knowledge of regulatory compliance requirements for AI/ML model deployment particularly in the financial sector.
Benefits
- Competitive salary and performancebased bonuses.
- Comprehensive insurance plans.
- Collaborative and supportive work environment.
- Chance to learn and grow with a talented team.
- A positive and fun work environment.
Proven experience as a Data Scientist or similar role. Strong knowledge of data analysis, statistics, and machine learning. Proficiency in data science tools and programming languages such as Python, R, Azure Data-bricks, SQL, etc. Familiarity with: Supervised and unsupervised learning techniques Deep learning and reinforcement learning Evaluation metrics, feature engineering, model selection and validation, ensemble methods, and explainable AI Category/Product Analytics,Store Analytics,Marketing and Promotion Analytics,Customer Analytics Expertise in visualization tools such as Power BI, Spot fire, or similar. Excellent storytelling skills to explain complex data to non-technical/business teams Experience in analytics, preferably within Retail, CPG, or E-commerce domains. Excellent communication and collaboration skills with the ability to work effectively in a team environment.