Data Scientist

As a highly motivated and experienced data scientist, you will lead a team of Gen-Ai Engineers, overseeing all processes from data extraction and pre-processing to training models and deploying them into production. Your passion for artificial intelligence and staying updated with the latest developments in the field will be crucial for this role. Key Responsibilities: - Utilize frameworks like Langchain for developing scalable and efficient AI solutions. - Integrate vector databases such as Azure Cognitive Search, Weavite, or Pinecone to enhance AI model functionalities. - Collaborate with cross-functional teams to define problem statements and prototype solutions using generative AI. - Ensure the robustness, scalability, and reliability of AI systems by implementing best practices in machine learning and software development. - Explore and visualize data to gain insights, identify data distribution differences affecting model performance, and devise strategies to overcome them. - Devise and oversee data-centered projects, ensuring data quality through cleaning and acquisition processes. - Find and utilize available datasets for training, define validation strategies, and engineer data augmentation pipelines. - Train models, tune hyperparameters, analyze model errors, and deploy models to production. Qualifications and Education Requirements: - Bachelors/Masters degree in computer science, data science, mathematics, or a related field. - 5-10 years of experience in building Gen-Ai applications. Preferred Skills: - Proficiency in statistical techniques for extracting insights and making predictions from data. - Strong skills in TensorFlow, PyTorch, Keras, and deep learning frameworks. - Specialization in Deep Learning (NLP) and statistical machine learning. - Proficiency in Python, with experience in developing production-grade applications. - Familiarity with Langchain framework, Azure Cognitive Search, Weavite, or Pinecone vector databases. - Understanding and experience with retrieval algorithms. - Experience with Big data platforms like Apache Hadoop, Spark, Kafka, Hive, for processing and analyzing large volumes of data efficiently. - Familiarity with deploying applications on Ubuntu/Linux systems. - Excellent communication, negotiation, and interpersonal skills.,