Data Scientist

Key Responsibilities: Develop, deploy, and maintain traditional machine learning models for predictive analytics, classification, clustering, and recommendation systems. Research, develop, and fine-tune Generative AI models (e.g., GPT, GANs, VAEs) for text generation, image synthesis, and other creative applications. Collaborate with cross-functional teams to understand business requirements, translate them into data-driven solutions, and communicate findings effectively. Implement and optimize deep learning architectures, including CNNs, RNNs, and Transformer-based models like BERT, GPT, and others. Analyze large datasets using statistical techniques and machine learning algorithms to identify trends, patterns, and actionable insights. Create and manage data pipelines, ensure data quality, and automate data collection processes. Stay up-to-date with the latest AI trends, tools, and technologies, including innovations in Generative AI, NLP, and deep learning. Design and conduct experiments to validate models and assess their performance across multiple dimensions. Collaborate with DevOps and engineering teams to deploy AI models into production environments, ensuring scalability and robustness. Mentor junior data scientists and contribute to the continuous learning culture within the team.
Skills and Qualifications: Proficiency in Python, R, or other relevant programming languages used in data science and machine learning. Strong background in traditional machine learning algorithms (e.g., regression, decision trees, random forests, SVMs, etc.) and statistical analysis. Expertise in deep learning frameworks such as TensorFlow, PyTorch, or Keras, with experience in neural network architectures, including CNNs, RNNs, and Transformers. Hands-on experience with Generative AI models like GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and large language models like GPT and BERT. Solid understanding of natural language processing (NLP) techniques such as sentiment analysis, named entity recognition, machine translation, and summarization. Experience with cloud platforms (AWS, GCP, Azure) and using AI/ML services such as SageMaker or Vertex AI for deploying and scaling models. Familiarity with big data tools (e.g., Hadoop, Spark) and database technologies (e.g., SQL, NoSQL). Strong problem-solving skills, attention to detail, and ability to work with large, complex datasets. Excellent communication skills with the ability to present technical information to both technical and non-technical audiences. Experience with version control systems (e.g., Git) and agile methodologies for software development.
Education and Experience: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field. 3+ years of experience in data science, machine learning, or AI, with demonstrated success in building and deploying models in production. Prior experience working on Generative AI projects, such as text generation, image creation, or AI-driven creative applications. A strong portfolio of AI-related projects or contributions to open-source AI tools or research