Data & AI Analyst — Insights, NLP & Dashboards

IBM; United States; Hybrid; USD 140,000 - 190,000; Full time

Job summary

IBM Consulting in the United States is seeking a data and AI specialist to help clients harness hybrid cloud and AI capabilities. You will work across data engineering, ML, and governance to deliver scalable data solutions.

You will collaborate with business and technical teams to define use cases, build data pipelines, and implement generative AI features while ensuring data quality and compliance. The role emphasizes continuous learning, cross-functional teamwork, and delivering measurable

Qualifications

• ≥5 years of professional experience in Data, AI, ML or similar technical environment.
• Strong Python skills for ML and data analysis.
• Experience with relational and NoSQL databases.
• Knowledge of ML lifecycle and MLOps practices.
• Familiarity with Generative AI and NLP.
• Experience with Kibana/ELK and IBM Watson Assistant is a plus.
• Proficient in French and English, both spoken and written.

Responsibilities

• Analyse and valorise data, identify trends and improvement opportunities.
• Collaborate with domain experts, data scientists and data engineers to define use cases.
• Design and improve data pipelines for data collection, transformation and AI solutions.
• Develop data quality monitoring and model performance tracking.
• Create dashboards and reports to measure usage and business value of AI solutions.
• Ensure governance, security and regulatory compliance of data.
• Stay updated on AI methods and tools to propose innovative value ideas.

Skills

Python

Data analysis

NLP

MLOps

English proficiency

French proficiency

Education

Bachelor's degree

Master's degree

Tools

Kibana

ELK stack

Watson Assistant

Job description

IBM Consulting in the United States is seeking a data and AI specialist to help clients harness hybrid cloud and AI capabilities. You will work across data engineering, ML, and governance to deliver scalable data solutions.

You will collaborate with business and technical teams to define use cases, build data pipelines, and implement generative AI features while ensuring data quality and compliance. The role emphasizes continuous learning, cross-functional teamwork, and delivering measurable