Engage in hands-on development, focusing on Time Series Analysis, Forecasting, and GenAI technologies.
Develop AIOps capabilities for IBM Cloud-based SaaS applications.
Lead design efforts and actively participate in coding at all levels, working closely with Architects
Operate within an Agile framework, ensuring continuous delivery.
Define development standards, including technology selection and workflow processes.
Collaborate with professionals to establish both functional and non-functional requirements.
Take part in technical reviews, including the assessment of requirements, specifications, designs, and other project artifacts.
Required Technical and Professional Expertise
Minimum of 10 years of industry experience in a Data Scientist role, with hands-on development experience.
Proficiency in Python programming.
Expertise in Time Series Analysis and Forecasting.
Demonstrated experience in AI projects, including familiarity with AI and machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch, LLMs, NLP, GenAI).
Skills in Anomaly Detection, Classification, Clustering, Optimization, and AI/AIOps.
Knowledge in AI model deployment and integration.
Experience with RESTful APIs and GitHub.
Basic understanding of Java.
Strong problem-solving capabilities, with the ability to adapt to a dynamic, fast-paced environment.
Excellent communication and teamwork abilities.
Preferred Technical and Professional Expertise
Data Engineering background.
Advanced experience with cloud technologies, including Kubernetes, microservices architecture, Kafka, Object Storage, Cassandra database, and Docker. Familiarity with IBM Cloud Technologies is a plus.