Job Opportunities API

Role Summary As a Data Scientist (Generative AI) , you will join a dynamic team responsible for building intelligent AI-driven applications such as virtual assistants and process optimization tools. Your role is essential in enhancing customer experience, optimizing internal workflows, and delivering smart automation solutions using cutting-edge AI techniques. Responsibilities • Design and develop innovative Generative AI applications for diverse business use cases. • Leverage analytical methodologies, including generative AI (GenAI) and predictive AI, to solve real-world challenges. • Work with techniques like Prompt Engineering, Retrieval-Augmented Generation (RAG), fine-tuning pre-trained models, speech-to-text, agent-based AI, and image processing. • Collaborate in an Agile team environment to develop production-ready AI applications. • Utilize rich datasets to build models that create real business impact. • Present insights and outcomes to senior management and key stakeholders. • Continuously learn and adapt to new AI/ML technologies and tools. Required Skills & Experience • Minimum 3 years of hands-on experience in Data Science and Machine Learning. • Strong proficiency in Python and deep learning frameworks. • Proven experience in developing and deploying Generative AI applications . • Solid understanding of model lifecycle, pre-trained models, and model fine-tuning. • Experience working with structured and unstructured data sources. • Ability to work autonomously and drive AI initiatives from concept to production. Preferred Tools & Technologies • GenAI frameworks : LangChain, Haystack • Version control : Git • ML platforms : Domino • Experience with AI applications in the Finance domain is a strong plus. Soft Skills • Strong team player and collaborator. • Quick self-starter with a proactive and business-oriented mindset. • Excellent communication and influencing skills. • Strong analytical and synthesis capabilities. • Commitment to innovation, ownership, and perseverance. • Adaptability to dynamic and multicultural work environments. Educational Background • Master’s degree in a quantitative field (e.g., Statistics, Mathematics, Engineering). • Candidates with other academic backgrounds and strong analytics experience are welcome to apply.