Technical Data Manager in Nokia's IP Routing Hardware team managing data entry and engineering change orders. Supporting NPI across product lines and implementing processes in manufacturing.
About the role
- Specialist in Data Science at Northern Trust designing and deploying agentic AI systems. Build ML pipelines and collaborate on advanced data science strategies with financial applications.
Responsibilities
- Design, build, and optimize agentic AI systems using modern agent frameworks.
- Implement multi-agent collaboration patterns, task orchestration, memory architectures, tool integrations, and reasoning-enhancing strategies.
- Develop secure, robust, and scalable tool-calling and function-execution flows for agents operating in dynamic environments.
- Architect and deploy RAG pipelines including document ingestion, text splitting, metadata extraction, query transformation, retrieval optimization, re-ranking, and grounding.
- Integrate RAG workflows with LLMs from OpenAI, Azure OpenAI, Anthropic, or open-source models.
- Build and maintain end-to-end ML pipelines including feature engineering, model training, hyperparameter tuning, and deployment.
- Conduct exploratory data analysis (EDA), statistical modeling, and experiment design.
- Implement MLOps practices for versioning, monitoring, and model governance.
- Build production-grade APIs and microservices for AI systems.
Requirements
- 7–8 years of industry experience in AI/ML engineering, data science, or full-stack AI solution architecture.
- Strong proficiency in Python, including libraries such as PyTorch, TensorFlow, LangChain/LangGraph, LlamaIndex, Hugging Face, and Scikit-learn.
- Deep understanding of LLMs, embeddings, vector search, and RAG best practices.
- Experience with agentic AI architectures, tool-calling, and autonomous agent design.
- Hands-on experience with cloud-based AI services (Azure AI, AWS SageMaker, GCP Vertex AI).
- Strong data engineering fundamentals (Spark, SQL, ETL pipelines).
- Experience deploying AI systems in production using containers (Docker), Kubernetes, or serverless architectures.
Benefits
- Reasonable accommodation for individuals with disabilities
- Flexible and collaborative work culture
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Petroleum Data Scientist providing predictive analytics and BI support for Oil and Gas company. Collaborating across departments to foster a data - driven culture and develop reporting tools.
Data Scientist leading and scaling data science initiatives for drug discovery at AQEMIA. Collaborating within the interdisciplinary Platform department to optimize molecule search methods.
Data Scientist in AI product organization at Candescent transforming digital banking. Engaging in data analysis and product strategy to deliver innovative solutions for financial institutions.
AI Specialist at M. Dias Branco building multi - agent solutions with focus on data integration and business optimization. Responsible for evolving and maintaining production systems and developing APIs.
Staff Data Scientist designing and implementing data science models for PayPal. Collaborating with stakeholders to support business needs and mentoring junior data scientists.
Senior Data Scientist developing and executing machine learning models for PG&E, focusing on risk mitigation and operational decision - making in safety and regulatory contexts.
Data Scientist in Supply Chain Analytics for Ford Motor Company. Leveraging technology and analytics to redefine transportation and enhance customer experience.
Data Scientist role focusing on predictive modeling and analytics for Ipsos NA projects. Collaborating with stakeholders to optimize business processes and improve data - driven insights.
Real - World Data Senior Data Scientist leveraging oncology data to drive insights for Labcorp’s initiatives. Collaborating with software engineers and clinicians to extract clinical insights from complex data assets.