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Senior Data Scientist - Artificial Intelligence
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Introduction In this role, you’ll work in one of our IBM Consulting Client Innovation Centers, where you will provide technical leadership and serve as a key reference point for complex AI initiatives across diverse industries.
A career in IBM Consulting is built on long-term relationships and close collaboration with global clients. As a Senior Data Scientist, you will contribute to shaping the client’s AI strategy, accelerating impact through IBM’s technology platforms and partner ecosystem.
Curiosity and continuous growth are core to our culture. In this role, you will be expected to drive innovation, propose unconventional approaches, and support the development of junior and mid-level team members.
Your Role And Responsibilities
Lead cross-functional collaboration with business stakeholders, data engineers, and technical teams, driving the definition of data-driven problems and opportunities.
Provide technical leadership, promoting quality standards, code reviews, experimentation, and best practices across the team.
Oversee complex data quality investigations and model performance issues, ensuring scalability, robustness, and long-term maintainability.
Design, develop, and validate advanced machine learning solutions, including supervised, unsupervised, and deep learning approaches that deliver measurable business impact.
Coordinate and optimize data preprocessing, feature engineering, and in-depth exploratory data analysis, establishing efficient and reproducible workflows.
Produce and review high-quality technical documentation, ensuring alignment with data architectures, internal standards, and compliance requirements.
Preferred Education Bachelor's Degree
Required Technical And Professional Expertise
Minimum 6 years of professional experience as a Data Scientist, with demonstrated ownership of end-to-end AI/ML projects in enterprise environments.
Academic background in data science, statistics, computer science, or related disciplines. A Master’s degree or advanced specialization is a plus.
Strong command of machine learning, advanced statistical methods, model evaluation, and optimization techniques.
Proven ability to lead technical teams and projects, identifying bottlenecks, defining priorities, and ensuring delivery excellence.
Strong understanding of data modeling concepts and relational/NoSQL database principles.
Advanced proficiency in Python and SQL, including ML frameworks such as scikit-learn, PyTorch, or TensorFlow.
Hands-on experience deploying models into production, including MLOps practices (CI/CD, monitoring, drift management, reproducibility).
Interest in earning advanced cloud or ML certifications (AWS/GCP/Azure), or possession of relevant certifications already.
Preferred Technical And Professional Experience
Agile mindset, adaptability, initiative, and strong critical thinking.
One Of The Following
In-depth understanding of data governance principles and data lifecycle management.
Significant experience with advanced data visualization and data storytelling, supporting executive-level decision-making.
Familiarity with cloud-based ML pipelines, distributed training, and scalable deployment technologies.
Advanced knowledge of statistical analysis, complex ML algorithms, and large-scale data processing techniques.
Availability to travel is required.
Seniority level Mid-Senior level
Employment type Full-time
Job function Engineering and Information Technology
Industries IT Services and IT Consulting
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