Masters degree or greater in data science, ML, or operational research, or 2 years of highly relevant industry experience(required) 0-2 years working on production ML or optimization software products at scale (required) Role: Data Scientist: Candidates need to travel to Europe once in a month (European country) Notes: We need someone who doesnt need visa to travel to Europe Experience above 10 years of experience mandatory Tell me about an optimisation problem you have solved? Business problem the context of it? explain what the measure was what were the constraints which algorithm have you used to solve this? what was your end result Data Scientist: We are seeking a highly skilled Data Scientist AI to design, develop, and deploy advanced machine learning and artificial intelligence solutions. The ideal candidate will work on large datasets, build predictive models, and collaborate cross-functionally to deliver scalable, data-driven products. Key Responsibilities Design, develop, and optimize machine learning and deep learning models. Work on AI/ML projects including NLP, computer vision, recommendation systems, and generative AI. Perform data cleaning, feature engineering, and exploratory data analysis (EDA). Build and manage data pipelines and model training workflows. Deploy models into production and monitor performance. Collaborate with Product, Engineering, and Business teams to translate business problems into AI solutions. Conduct model evaluation, A/B testing, and performance tuning. Document models, experiments, and technical processes. Required Skills & Qualifications Classic Machine learning (Regression, predictive Analysis, Classification, Clustering) Machine learning Model Optimisation Strong proficiency in Python (NumPy, Pandas, Scikit-learn). Hands-on experience with Deep Learning frameworks: TensorFlow, PyTorch, or Keras. Experience in Natural Language Processing (NLP) and/or Computer Vision. Strong knowledge of Machine Learning algorithms and statistics. Experience with SQL/NoSQL databases and big data tools (Spark, Hadoop preferred). Experience with MLOps tools such as Docker, Kubernetes, CI/CD pipelines. Preferred Skills Experience with LLMs / Generative AI (OpenAI, Hugging Face, LangChain). Cloud experience (AWS, Azure, or GCP). Experience building AI APIs and microservices.