Job Description
Job DescriptionWe are looking for a skilled Generative AI Analyst/Prompt Engineer to join our team on a contract basis in New York, New York. In this role, you will leverage your expertise in data science and artificial intelligence to develop and optimize innovative solutions. This position is an excellent opportunity to work in the financial services industry while applying cutting-edge AI technologies to real-world challenges.
Responsibilities:
• Design, implement, and optimize AI-driven models and solutions tailored to business needs.
• Develop and maintain scalable data pipelines and workflows using tools like Apache Kafka, Spark, and Hadoop.
• Write and debug Python code, utilizing Jupyter Notebooks for effective data analysis and visualization.
• Collaborate with cross-functional teams to integrate AI models into existing systems and workflows.
• Research and experiment with state-of-the-art generative AI techniques to improve system performance.
• Build and manage APIs to facilitate seamless communication between applications and AI models.
• Utilize cloud-based technologies, including AWS, to deploy, scale, and monitor AI solutions.
• Visualize complex data insights through effective data visualization techniques and tools.
• Implement algorithms that solve specific business problems in a robust and efficient manner.• At least 5 years of experience in data science, software development, or a related technical field, demonstrating attention to detail.
• A minimum of 2 years of hands-on experience working with generative AI technologies.
• Proficiency in Python programming and experience working with Jupyter Notebooks.
• Strong knowledge of big data tools, including Apache Kafka, Spark, Pig, and Hadoop.
• Familiarity with cloud platforms such as AWS for deploying and managing solutions.
• Expertise in data visualization techniques and tools to present analytical findings.
• Proven ability to develop APIs and integrate them into various systems.
• Solid understanding of algorithm development and implementation for real-world applications.