DS – Graph neural network expert
Job Description
<p>· <strong>MUST submit a Resume in English, to : </strong>hr@ckcodeconnect</p><p>· <strong>E-mail Subject should include you full name | position</strong></p><p>· <strong>Fluency in English is a must</strong></p><p>· <strong>Working hours PST.</strong></p><p><br></p><p><strong>About the company:</strong></p><p>Yobi is a fast-growing tech company focused on developing AI-based software solutions that support the marketing and communications needs of small businesses and large corporations. Our cutting-edge technology empowers businesses to optimize their marketing strategies and enhance customer engagement. We are committed to pushing the boundaries of artificial intelligence and leveraging data-driven insights to drive business success.</p><p> </p><p><strong>About the position:</strong></p><p> We are currently seeking a talented and experienced Data Scientist with expertise in Graph Neural Networks to join our dynamic team and contribute to our exciting projects.</p><p>As a DS – Graph Neural Network Expert at Yobi, you will play a pivotal role in designing, developing, and implementing advanced AI solutions using Graph Neural Networks (GNNs).</p><p>You will work closely with our team of data scientists, engineers, and researchers to build high-performance models that can analyze and extract insights from complex, interconnected datasets.</p><p>Your expertise in GNNs will enable us to develop intelligent systems capable of understanding relationships, patterns, and structures within the data.</p><p><br></p><p><strong>Responsibilities:</strong></p><p>- Research, design, and implement state-of-the-art Graph Neural Network models and algorithms to solve complex problems.</p><p>- Develop innovative solutions for various AI-based applications, such as recommendation systems, fraud detection, knowledge graph analysis, social network analysis, and more.</p><p>- Collaborate with cross-functional teams to identify business requirements and translate them into technical specifications.</p><p>- Analyze and preprocess large-scale graph data, ensuring data quality, integrity, and efficiency.</p><p>- Train, fine-tune, and optimize GNN models using cutting-edge techniques to improve performance and scalability.</p><p>- Conduct thorough experiments and evaluations to assess model performance, accuracy, and robustness.</p><p>- Stay up-to-date with the latest advancements in Graph Neural Networks and related fields, such as deep learning, reinforcement learning, and natural language processing.</p><p>- Actively contribute to research papers, patents, and open-source projects to showcase thought leadership and promote the company’s reputation in the AI community.</p><p><br></p><p><strong>Requirements:</strong></p><p>- Master’s or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field.</p><p>- Solid understanding of graph theory and network analysis.</p><p>- Strong background in machine learning and deep learning techniques, with a focus on Graph Neural Networks.</p><p>- Proficiency in programming languages such as Python, TensorFlow, PyTorch, or similar frameworks.</p><p>- Experience with graph data processing and graph database technologies (e.g., Neo4j, Amazon Neptune, Apache Giraph) is highly desirable.</p><p>- Familiarity with cloud computing platforms (e.g., AWS, Google Cloud, Azure) and distributed computing frameworks (e.g., Apache Spark) is a plus.</p><p>- Excellent problem-solving skills, with the ability to tackle complex challenges and develop creative solutions</p><p> - Strong communication skills and ability to collaborate effectively in a multidisciplinary team.</p><p>- Demonstrated track record of research contributions in the field of Graph Neural Networks, evidenced by publications, conference presentations, or relevant projects.</p><p><br></p><p></p>
