Data Scientist - I

Job Responsibilities:

• Design and implement machine learning algorithms for NLP/LLMs or deep learning models at scale to meet business requirements.
• Analyze large datasets and develop models that can be used to make predictions, generate responses or summaries, identify patterns etc.
• Develop and improve existing models to increase accuracy, efficiency, and effectiveness.
• Work closely with cross-functional teams to identify and prioritize business problems, and develop solutions to address them.
• Communicate findings and insights to stakeholders in a clear and concise manner.
• Stay up-to-date with the latest developments in machine learning, NLP/LLMs, deep learning, and related technologies.

Requirements:

• Bachelor’s or Master’s degree in Applied Mathematics, Statistics,  Computer Science or another quantitative field.
• 2+ years of experience in Data Science or a related field, with a focus on building NLP/LLMs or Deep Learning models.
• Strong programming skills in Python or other relevant programming languages.
• Experience with machine learning libraries such as TensorFlow, PyTorch, or Keras.
• Experience working with a variety of statistical models, including logistic regression, clustering, classification, SVMs, neural networks, Random Forest, CRF, Bayesian models, supervised/unsupervised learning, etc.
• Expertise in NLP techniques, including sentiment analysis, word embedding, part-of-speech (POS) tagging, topic modeling, text classification, machine translation, speech recognition, named entity recognition (NER), natural language generation (NLG), and other related techniques.
• Experience with various deep learning techniques, including CNNs and RNNs, and a strong understanding of building and training these models for different applications. Familiarity with LMs and LLMs such as GPT, BERT, and Transformer models is highly desirable.
• Strong ability to rapidly comprehend and implement research papers related to AI, as well as remain informed of the latest advancements in NLP technologies.
• Deep knowledge and experience in structured and unstructured data Information Extraction, Knowledge Information Retrieval, and Knowledge Representation.
• Self-motivated and driven to satisfy intellectual curiosity through the pursuit of continuous learning and skill development.
• Strong problem-solving and analytical skills
• Excellent communication and collaboration abilities.
• Optional: Experience with big data platforms such as Hadoop or Spark.