2.0 - 6.0 years

0 Lacs

maharashtra

On-site

AryaXAI stands at the forefront of AI innovation, revolutionizing AI for mission-critical, highly regulated industries by building explainable, safe, and aligned systems that scale responsibly. The mission of AryaXAI is to create AI tools that empower researchers, engineers, and organizations, including banks, financial institutions, and large enterprises, to unlock AI's full potential while maintaining transparency, safety, and regulatory compliance. The team at AryaXAI thrives on a shared passion for cutting-edge innovation, collaboration, and a relentless drive for excellence. Each team member contributes hands-on in a flat organizational structure that values curiosity, initiative, and exceptional performance, ensuring that the work not only advances technology but also meets the rigorous demands of regulated sectors. As a Senior Data Scientist at AryaXAI, you will be uniquely positioned to tackle large-scale, enterprise-level challenges in regulated environments. You will lead complex AI implementations that prioritize explainability, risk management, and compliance, directly impacting mission-critical use cases in the financial services industry and beyond. Your expertise will be crucial in deploying sophisticated models that address the nuances and stringent requirements of regulated sectors. Responsibilities include: - Model Evaluation & Customization - Architectural Assessment - Enterprise Integration - Advanced AI Techniques - Specialization & Innovation - Collaboration & Quality Assurance - Documentation & Compliance Qualifications: - Educational & Professional Background - Regulated Industry Experience (FS, Banking or Insurance is preferred) - Technical Expertise - Diverse Data Handling - Deployment Proficiency - Publications & Contributions A solid academic background in machine learning, deep learning, or reinforcement learning, ideally complemented by experience in regulated industries such as financial services or enterprise sectors, is required. The ideal candidate will have a proven track record (2+ years) of hands-on experience in data science within highly regulated environments, with a deep understanding of the unique challenges and compliance requirements in these settings. Demonstrated proficiency with deep learning frameworks (TensorFlow, PyTorch, etc.) and experience in implementing advanced techniques (Transformer models, GANs, etc.) is essential. Experience working with varied data types, including textual, tabular, categorical, and image data, and the ability to develop models that handle complex, enterprise-level datasets is also required. Expertise in deploying AI solutions in both cloud and on-premise environments, ensuring robust, scalable, and secure integrations with enterprise systems, is a key qualification. Peer-reviewed publications or significant contributions to open-source tools in AI are highly regarded.,

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