Why Join IBM?
At IBM, you’ll be part of a global team that’s redefining what’s possible with AI and data. You’ll have access to cutting-edge tools, a collaborative culture, and opportunities to shape the future of technology and business.
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. You’ll also be a key contributor leading business development through proposal writing, solutioning, and client presentations.
Key Responsibilities
- Strategic leadership of large end-to-end AI solutions, advanced analytics and automation engagements from discovery to deployment.
- Act as a trusted advisor to senior client stakeholders, translating business challenges into data-driven solutions and articulating the value of AI.
- Translate complex data into actionable insights and strategic recommendations.
- Collaborate with cross-functional teams including consultants, engineers, and client stakeholders, fostering a culture of innovation, collaboration, and continuous learning.
- Design and implement machine learning models, statistical analyses, and AI solutions tailored to client needs.
- Lead business development through proposal writing, solutioning, and client presentations.
- Contribute to IBM’s thought leadership by publishing white papers, speaking at conferences, and developing reusable assets and accelerators.
- Mentor and coach junior data scientists and analysts.
- Stay current with emerging technologies and methodologies in AI/ML and data science.
- Proven experience (8+ years) in delivering AI solutions, advanced analytics and automation solutions in a consulting or enterprise environment.
- Excellent communication and stakeholder management skills.
- Experience leading cross-functional teams and mentoring talent.
- Strong understanding of machine learning, deep learning, NLP, and statistical modelling.
- Experience with cloud platforms (IBM Cloud, AWS, Azure, or GCP).
- Experience working with clients in sectors such as financial services, healthcare, or public sector is desirable.
- PhD or equivalent experience is a plus. (preferable in Data Science, Computer Science, Statistics, or a related field)
- Certifications in cloud platforms or data science tools (e.g., IBM Data Science Professional Certificate) are advantageous.
- Experience with data engineering tools and MLOps practices is a plus