Candidates should possess a Bachelor's degree and a minimum of 7 years of experience in customer success, preferably within the life sciences industry. Strong experience in strategic account management, stakeholder engagement, and driving customer adoption is essential. Demonstrated ability to manage complex projects and collaborate with cross-functional teams is also required.
Candidates should possess hands-on data engineering experience, a visionary approach to system building, a strong track record of creating scalable systems and pipelines, the ability to work independently and navigate complex challenges, experience in cross-functional collaboration and strategic alignment, clear communication skills, and the ability to solve complex data problems and deliver innovative solutions.
Candidates should possess 6+ years of experience in data engineering, working with large-scale data systems and pipelines, and a strong understanding of Large Language Models (LLMs) and their applications. Familiarity with model training and fine-tuning, particularly in NLP (Natural Language Processing) contexts, is beneficial, along with basic knowledge of network, security, and encryption protocols such as HTTP/HTTPS/TLS.
Candidates should have 1–2 years of professional experience, strong programming skills in TypeScript, Node.js, and Python, practical experience with Docker and Kubernetes, and familiarity with Big Data technologies like Scala, Hadoop, PySpark, Golang, GraphQL, Elasticsearch, and LLMs.