As a Senior Data Scientist at Netomi, you will drive NLP and machine learning projects and be responsible for developing methodology and solutions to support technical, analytical and operational requirements.
Job Responsibilities
Design, develop and deploy machine learning models and algorithms for NLP/LLMs or deep learning models at scale to solve complex business problems.
Work with large datasets, perform data analysis and develop data pipelines to support model development.
Collaborate with Product & Engineering teams to integrate machine learning solutions into products and services.
Conduct experiments, test hypotheses, and perform statistical analysis to validate models and drive improvements.
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.
Provide technical mentorship and guidance to junior team members.
Requirements
3+ years of experience as a data scientist, preferably in a product development environment, 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 (eg, scikit-learn, TensorFlow, PyTorch).
Deep understanding of statistical analysis, probability theory, and experimental design.
Experience with LLMs, deep learning, NLP and chatbot development.
Excellent communication skills, including the ability to explain complex concepts to technical and non-technical stakeholders.
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 we'll 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.
Optional: Experience with large-scale data processing technologies (eg, Hadoop, Spark) and distributed computing systems.