Lead Data Scientist - AI and Machine Learning

As an Associate Lead Data Scientist at YASH Technologies, you will be leading our AI and data science initiatives by designing, developing, and deploying advanced machine learning and AI solutions. You will work closely with a team of data scientists and engineers to ensure best practices in data science, MLOps, and scalable AI systems. Your responsibilities will include:

- Designing and implementing advanced machine learning, deep learning, and AI models in areas such as NLP, computer vision, recommendation systems, and generative AI. - Overseeing data strategy, including preprocessing, feature engineering, and large-scale data pipelines. - Driving the adoption of MLOps best practices for model development, deployment, and monitoring. - Leading and mentoring a team of data scientists, ML engineers, and analysts. - Collaborating with stakeholders to understand business problems and define data-driven solutions. - Staying updated with the latest advancements in AI/ML and evaluating their potential application. - Ensuring that models are explainable, ethical, and compliant with regulatory requirements. • *Primary (Must-Have) Skills:** - Strong foundation in Mathematics, Statistics, and Machine Learning theory. - Proficiency in Python and ML frameworks such as scikit-learn, TensorFlow, PyTorch, and Hugging Face. - Proven expertise in NLP, Computer Vision, or Generative AI using technologies like Transformers, RAG, LLMs, CNNs, and Vision Transformers. - Hands-on experience with Big Data technologies like Spark, Hadoop, Kafka, and Hive. - Strong knowledge of SQL and data pipelines. - Experience with cloud platforms such as Azure ML, AWS SageMaker, or GCP AI Platform. - Understanding of MLOps practices including CI/CD, Docker, Kubernetes, and model monitoring. • *Secondary (Good-to-Have) Skills:** - Programming experience in Java, Scala, or R. - Familiarity with web/backend integration using REST APIs, Django, FastAPI, or Spring Boot. - Knowledge of data governance, ethics, and compliance in AI. - Strong business acumen and the ability to translate insights into strategies. - Excellent communication, leadership, and stakeholder management skills. • *Qualifications:** - Bachelors/Masters/PhD in Computer Science, Statistics, Mathematics, Data Science, or related field. - 7+ years of experience in Data Science/AI, with at least 23 years in a leadership role. - Proven track record of delivering AI/ML projects at scale in production environments.

At YASH Technologies, you will have the opportunity to shape your career in an inclusive team environment. Our Hyperlearning workplace is grounded upon principles of flexible work arrangements, agile self-determination, trust, transparency, open collaboration, all support needed for business goals realization, stable employment, great atmosphere, and ethical corporate culture. Join us and be part of our journey towards creating real positive changes in the virtual world. As an Associate Lead Data Scientist at YASH Technologies, you will be leading our AI and data science initiatives by designing, developing, and deploying advanced machine learning and AI solutions. You will work closely with a team of data scientists and engineers to ensure best practices in data science, MLOps, and scalable AI systems. Your responsibilities will include:

- Designing and implementing advanced machine learning, deep learning, and AI models in areas such as NLP, computer vision, recommendation systems, and generative AI. - Overseeing data strategy, including preprocessing, feature engineering, and large-scale data pipelines. - Driving the adoption of MLOps best practices for model development, deployment, and monitoring. - Leading and mentoring a team of data scientists, ML engineers, and analysts. - Collaborating with stakeholders to understand business problems and define data-driven solutions. - Staying updated with the latest advancements in AI/ML and evaluating their potential application. - Ensuring that models are explainable, ethical, and compliant with regulatory requirements. • *Primary (Must-Have) Skills:** - Strong foundation in Mathematics, Statistics, and Machine Learning theory. - Proficiency in Python and ML frameworks such as scikit-learn, TensorFlow, PyTorch, and Hugging Face. - Proven expertise in NLP, Computer Vision, or Generative AI using technologies like Transformers, RAG, LLMs, CNNs, and Vision Transformers. - Hands-on experience with Big Data technologies like Spark, Hadoop, Kafka, and Hive. - Strong knowledge of SQL and data pipelines. - Experience with cloud platforms such as Azure ML, AWS SageMaker, or GCP AI Platform. - Understanding of MLOps practices including CI/CD, Docker, Kubernetes, and model monitoring. • *Secondary (Good-to-Have) Skills:** - Programming experience in Java, Scala, or R. - Familiarity with web/backend integration using REST APIs, Django, FastAPI, or Spring Boot. - Knowledge of data governance, ethics, and compliance in AI. - Strong busi