Sr Data Scientist

As a Senior Data Scientist in the Data & Analytics field, you will be responsible for a variety of tasks that involve advanced analytics, modeling, data strategy, engineering collaboration, business impact, AI strategy, thought leadership, mentorship, and technical expertise. You will design and implement advanced machine learning models, including deep learning, time-series forecasting, recommendation engines, and LLM-based solutions such as GPT, LLaMA, and Claude. Additionally, you will develop use cases around enterprise search, document summarization, conversational AI, and automated knowledge retrieval using large language models. Your role will also involve fine-tuning or prompt-engineering foundation models for domain-specific applications and evaluating and optimizing LLM performance, latency, cost-effectiveness, and hallucination mitigation strategies for production use. Collaboration with data and ML engineering teams will be crucial as you work closely to integrate LLM-powered applications into scalable, secure, and reliable pipelines. You will contribute to the development of retrieval-augmented generation architectures using vector databases and support the deployment of models using MLOps principles. Partnering with cross-functional stakeholders, you will identify opportunities for applying LLMs and generative AI to solve complex business challenges. Leading workshops or proofs-of-concept will be part of your responsibilities to demonstrate the value of LLM use cases across business units. You will also translate complex model outputs into clear insights and decision support tools for non-technical audiences. As an internal thought leader on AI and LLM innovation, you will keep the organization at the forefront of industry advancements. Mentoring and upskilling data science team members in advanced AI techniques and contributing to strategic roadmaps for generative AI and model governance within the enterprise will be key aspects of your role. To qualify for this position, you should have education in Data Science, Artificial Intelligence, Computer Science, or related quantitative discipline, along with 5+ years of hands-on experience in data science. Demonstrated success in deploying machine learning and NLP solutions at scale and proven experience with cloud AI platforms are required. Proficiency in Python and SQL, experience with prompt engineering, fine-tuning, and LLM orchestration tools, familiarity with data storage and retrieval systems, and strong understanding of model evaluation techniques for generative AI are also necessary. Additionally, you should possess leadership skills and be a strategic thinker with the ability to align AI initiatives to business goals. Excellent communication and storytelling skills are crucial for articulating the value of LLMs and advanced analytics. Strong collaboration skills and the ability to influence stakeholders across various teams are also essential. Preferred qualifications for this role include experience with IoT, edge analytics, or smart building systems, familiarity with LLMOps, LangChain, Semantic Kernel, or similar orchestration frameworks, and knowledge of data privacy and governance considerations specific to LLM usage in enterprise environments.,