IBM Data Scientist Job Openings 2025 | Advanced Analytics

Qualifications

Required education: Bachelor’s Degree

Preferred education: Master’s Degree

Required technical and professional expertise

• Proof of Concept (POC) Development: Develop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions.
• Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another
• Document solution architectures, design decisions, implementation details, and lessons learned.
• Stay up to date with the latest trends and advancements in AI, foundation models, and large language models.
• Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation

Preferred technical and professional experience

• Experience and working knowledge in COBOL & JAVA would be preferred
• Having experience in Code generation, code matching & code translation leveraging LLM capabilities would be a Big plus
• Demonstrate a growth mindset to understand clients’ business processes and challenges.

Job Description & Responsibilities:

As an Data Engineer at IBM you will harness the power of data to unveil captivating stories and intricate patterns. You’ll contribute to data gathering, storage, and both batch and real-time processing.

Collaborating closely with diverse teams, you’ll play an important role in deciding the most suitable data management systems and identifying the crucial data required for insightful analysis. As a Data Engineer, you’ll tackle obstacles related to database integration and untangle complex, unstructured data sets.

In this role, your responsibilities may include:

• Implementing and validating predictive models as well as creating and maintain statistical models with a focus on big data, incorporating a variety of statistical and machine learning techniques
• Designing and implementing various enterprise search applications such as Elasticsearch and Splunk for client requirements
• Work in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviour’s.
• Build teams or writing programs to cleanse and integrate data in an efficient and reusable manner, developing predictive or prescriptive models, and evaluating modelling results