Data Scientist - AI - Managing Consultant

Job description

from IBM careers

Introduction

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

Your role and responsibilities

As a Data Scientist at IBM, you will lead the design and delivery of AI solutions, advanced analytics and automation for clients across industries. You will work at the intersection of data science, business strategy, and technology, helping clients unlock value from their data assets while mentoring junior team members and shaping IBM’s data science capability.

• Lead end-to-end AI solutions, advanced analytics and automation engagements from discovery to deployment.
• Translate complex data into actionable insights and strategic recommendations.
• Collaborate with cross-functional teams including consultants, engineers, and client stakeholders.
• Design and implement machine learning models, statistical analyses, and AI solutions tailored to client needs.
• Contribute to business development through proposal writing, solutioning, and client presentations.
• Mentor and coach junior data scientists and analysts.
• Stay current with emerging technologies and methodologies in AI/ML and data science.

 

Required technical and professional expertise

• Full AI Project Lifecycle: Experience in managing the full AI project lifecycle, from research and prototyping to deployment in production environments. Excellent communication and stakeholder management skills.
• Advanced Analytics Techniques: Experience with advanced analytics techniques for structured data, including proficiency in Python and AI frameworks such as TensorFlow, PyTorch, Keras, or Hugging Face.
• NLP and ML Methods: Deep understanding of Natural Language Processing (NLP) and Machine Learning (ML) methods for unstructured content, with expertise in foundation models and large language models.
• AI Solution Development: Experience in architecting and delivering AI solutions using cutting-edge technologies, including tools like Github Copilot and Amazon Code Whisperer.
• Cloud Platforms and Services: Familiarity with cloud platforms (e.g., Kubernetes, AWS, Azure, GCP, IBM Cloud) and related services, as well as experience with relational and NoSQL databases (SQL, Postgres, DB2, MongoDB).

 

Preferred technical and professional experience

• Foundation in Specialised Areas: Experience with one of the following areas: NLP, Image Processing, Video Processing, Voice Processing, or Watson technologies, enabling optimization of AI solutions and driving business value.
• Proficiency in Modern UI Frameworks: Familiarity with modern UI frameworks such as Backbone.js, AngularJS, React.js, Ember.js, Bootstrap, and JQuery, allowing for seamless integration with AI solutions.
• Operating System Knowledge: Experience working with various operating systems, including Linux, Windows, iOS, and Android, facilitating smooth deployment of AI solutions across different environments.
• PhD or equivalent experience is a plus (preferable in Data Science, Computer Science, Statistics, or a related field