Data Scientist

Responsibilities Collaborate with cross-functional teams to identify opportunities for AI and Data to solve business challengesDesign and implement data pipelines to collect, process, and integrate data from various sourcesDevelop and optimize machine learning and deep learning models for predictive analytics, computer vision, natural language processing, and moreLeverage big data technologies like Hadoop, Spark, and NoSQL databases to handle large-scale datasetsExplore and apply generative AI techniques to generate synthetic data, create content, and automate tasksImplement MLOps practices to streamline the model development lifecycle and enable continuous deploymentPresent findings and recommendations to stakeholders in a clear and compelling mannerLead cross-functional teams to deliver AI projects on time and within budgetStay current with the latest advancements in AI, data engineering, and related technologies Skills8+ years of experience in data science, machine learning, and AIProficiency in Python, SQL and data visualization tools like Tableau or PowerBIHands-on experience with machine learning frameworks like TensorFlow, PyTorch, or KerasKnowledge of deep learning architectures and techniques for computer vision, NLP, and generative AIHands-on experience with big data technologies such as Hadoop, Spark, and NoSQL databasesUnderstanding of MLOps principles and tools for model versioning, monitoring, and deploymentFamiliarity with Kubernetes core concepts like pods, deployments, services, and ingressStrong communication and leadership skills to effectively collaborate with cross-functional teamsAbility to work in a fast-paced, agile environment and adapt to changing priorities