Job description
Data Scientist We are looking for a Data Scientist with 4–8 years of experience in Machine Learning, Data Science, and expertise in Generative AI to develop intelligent solutions that solve real-world business problems. The role involves building predictive models, developing AI-powered applications, working with Large Language Models (LLMs), and collaborating with cross-functional teams to deliver scalable AI solutions. The ideal candidate should have a strong foundation in data science projects along with hands-on experience in modern AI technologies and cloud-based data platforms. Key Responsibilities Develop, train, and deploy Machine Learning and Deep Learning models for business use cases. Perform data analysis, feature engineering, model evaluation, and performance optimization. Build and enhance Generative AI solutions using LLMs, embeddings, and Retrieval-Augmented Generation (RAG) techniques. Design and implement AI workflows using frameworks such as LangChain and LangGraph. Integrate AI solutions with enterprise applications, APIs, databases, and data platforms. Collaborate with Data Engineers, Product Owners, Architects, and business stakeholders to deliver end-to-end AI solutions. Monitor and improve model performance, reliability, and scalability in production environments. Stay updated with emerging trends in AI, Machine Learning, and Generative AI technologies. Required Qualifications Bachelor’s or master’s degree in computer science, Data Science, Artificial Intelligence or a related field. 4–8 years of experience in Data Science, Machine Learning, and AI-related roles. Strong programming skills in Python, PySpark. Other languages are good to have. Experience working with LLMs, prompt engineering, embeddings, and RAG-based solutions. Knowledge of LangChain and/or LangGraph for AI application development. Strong SQL and data analysis skills. Experience working with cloud platforms such as Azure, AWS, or GCP. Preferred Skills Experience in delivering ML projects with deployment capabilities. Experience with vector databases and semantic search solutions. Exposure to Databricks, Spark, or large-scale data processing platforms. Familiarity with MLOps tools, Docker, and model deployment practices. Experience building AI assistants, copilots, or conversational AI applications. Key Competencies Strong analytical and problem-solving skills. Ability to work independently and collaboratively in a fast-paced environment. Effective communication and stakeholder management skills. Passion for innovation and continuous learning in AI and Data Science.
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