Senior Data Scientist – Agentic & Scalable AI Solutions

At Innover, we endeavor to see our clients become connected, insight-driven businesses. Our integrated Digital Experiences, Data & Insights and Digital Operations studios help clients embrace digital transformation and drive unique outstanding experiences that apply to the entire customer lifecycle. Our connected studios work in tandem to reimagine the convergence of innovation, technology, people, and business agility to deliver impressive returns on investments. We help organizations capitalize on current trends and game-changing technologies molding them into future-ready enterprises.

Take a look at how each of our studios represents deep pockets of expertise and delivers on the promise of data-driven, connected enterprises.

Seeking a highly skilled and motivated Data Scientist with a strong emphasis on Generative AI and Large Language Models (LLM). This role requires a unique blend of technical expertise and business insight to transition from promising hypotheses and ML experiments to fully-fledged AI/ML products with real-world impact. As a specialist in Generative AI techniques, you will work with innovative closed and open-source Gen AI models, apply standard methodologies in prompt engineering, RAG applications, and fine-tune LLM models to drive business outcomes.

Responsibilities:

• Develop and implement machine learning models, focusing on Generative AI techniques and LLM, to solve sophisticated business problems, using a variety of algorithms and techniques.
  
• Streamline Generative AI model development and deployment using Azure infrastructure and capabilities like cognitive search and Vectordb, and frameworks such as Langchain, Llama, Semantic Kernel, and Autogen.
  
• Apply prompt engineering techniques, work with RAG applications, and fine-tune language models to improve their performance in specific tasks.
  
• Collaborate with multi-functional teams to plan, scope, implement, and sustain predictive analytics solutions.
  
• Design and complete experiments to validate and optimize machine learning models, ensuring accuracy, efficiency, and scalability.
  
• Deploy machine learning models and applications on cloud platforms like Azure ML or Databricks, ensuring seamless integration, scalability, and cost-effectiveness.
  
• Develop measurements and feedback systems, and mentor associates and peers on MLOps & LLMOps standard methodologies.
  
• Stay up-to-date with the latest advancements in machine learning, generative AI, prompt engineering, RAG applications, and cloud technologies, and apply them to enhance our data science capabilities.

Requirements:

• Hands-on experience with Gen AI-related tech stack, including Azure cognitive search, Langchain, Semantic Kernel, and agent frameworks like Autogen, Vectordb.
  
• Hands on experience with predictive modelling around Credit risk
  
• Experience in fine-tuning open-source models like Llama, Phi2 is a bonus.
  
• Experience with Open AI APIs, Fine-tuning and Assistant APIs
  
• Proven experience as a Data Scientist, with a strong focus on machine learning, generative AI, prompt engineering, and RAG applications.
  
• Working knowledge of Cloud, Architecture, REST APIs to deploy inferencing and fine-tuning solutions.
  
• Strong partner management, ability to translate sophisticated technical topics into business language, presentation skills, and an ability to balance a sense of urgency with shipping high-quality and pragmatic solutions.
  
• Strong software development skills with proficiency in Python and advanced working SQL knowledge, preferably using the Azure stack and experience with Azure ML, Databricks, Azure Data Factory.
  
• Experience in product-ionizing code through the DevOps pipeline (git, Jenkins pipeline, code scan).
  
• Solid understanding of machine learning algorithms, statistical modeling, and data analysis techniques.