Data Scientist & Sr. Data Scientist

As a highly motivated and experienced data scientist, you will lead a team of Gen-Ai Engineers. Your responsibilities will include managing all processes from data extraction, cleaning, and pre-processing to training models and deploying them to production. The ideal candidate will be passionate about artificial intelligence and stay up-to-date with the latest developments in the field. 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 support AI model functionalities. - Work closely with cross-functional teams to define problem statements and prototype solutions leveraging generative AI. - Ensure robustness, scalability, and reliability of AI systems by implementing best practices in machine learning and software development. - Explore and visualize data to gain an understanding of it, then identify differences in data distribution that could affect performance when deploying the model in the real world. - Verify data quality and ensure it via data cleaning. - Supervise the data acquisition process if more data is needed. - Find available datasets online that could be used for training. - Define validation strategies, feature engineering data augmentation pipelines to be done on a given dataset. - Train models and tune their hyperparameters. - Analyze the errors of the model and design strategies to overcome them. - Deploy models to production. Qualifications and Education Requirements: - Bachelors/Masters degree in computer science, data science, mathematics, or a related field. - At least 3-10 years of experience in building Gen-Ai applications. Preferred Skills: - Proficiency in statistical techniques such as hypothesis testing, regression analysis, clustering, classification, and time series analysis to extract insights and make predictions from data. - Proficiency with a deep learning framework such as TensorFlow, PyTorch, and Keras. - Specialized in Deep Learning (NLP) and statistical machine learning. - Strong Python skills. - Experience with developing production-grade applications. - Familiarity with Langchain framework and vector databases like Azure Cognitive Search, Weavite, or Pinecone. - Understanding and experience with retrieval algorithms. - Worked on Big data platforms and technologies such as Apache Hadoop, Spark, Kafka, or Hive for processing and analyzing large volumes of data efficiently and at scale. - Familiarity in working and deploying applications on Ubuntu/Linux system. - Excellent communication, negotiation, and interpersonal skills.,