IBM is Hiring Data Scientist-Artificial Intelligence | Bangalore | Freshers

Job Description

IBM's 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐬𝐭-𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 opening is an interesting option for early-career candidates who want to move beyond conventional machine learning projects and work on AI solutions with a strong 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐚𝐧𝐝 𝐜𝐨𝐧𝐬𝐮𝐥𝐭𝐢𝐧𝐠 𝐚𝐧𝐠𝐥𝐞. The role combines data science with proof-of-concept development, meaning candidates are expected not only to build models but also to demonstrate how AI can solve a practical customer problem. Another unusual aspect is the exposure to 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈-𝐚𝐬𝐬𝐢𝐬𝐭𝐞𝐝 𝐜𝐨𝐝𝐞 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧, particularly around modernizing legacy COBOL applications into Java. That makes this opening broader than a typical entry-level data scientist position and potentially useful for candidates interested in 𝐀𝐈 𝐜𝐨𝐧𝐬𝐮𝐥𝐭𝐢𝐧𝐠, 𝐚𝐩𝐩𝐥𝐢𝐞𝐝 𝐦𝐚𝐜𝐡𝐢𝐧𝐞 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠, and 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧.

WHAT THE ROLE ACTUALLY INVOLVES:

The work appears to sit across three connected areas: understanding 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬, developing analytical or AI-based solutions, and turning promising ideas into 𝐰𝐨𝐫𝐤𝐢𝐧𝐠 𝐩𝐫𝐨𝐭𝐨𝐭𝐲𝐩𝐞𝐬. Candidates may work with large datasets, predictive or prescriptive approaches, and machine learning techniques before evaluating whether the resulting solution actually addresses the intended business requirement. The 𝐩𝐫𝐨𝐨𝐟-𝐨𝐟-𝐜𝐨𝐧𝐜𝐞𝐩𝐭 component is especially important because it requires moving from an idea to something demonstrable that development teams and customers can assess. For a fresher, the biggest learning curve will likely be connecting technical model development with business requirements and communicating results effectively to people who may not have a data science background.

SKILLS ANALYSIS:

𝐏𝐲𝐭𝐡𝐨𝐧 and practical 𝐦𝐚𝐜𝐡𝐢𝐧𝐞 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 knowledge are the core technical foundations for this position, with frameworks such as 𝐓𝐞𝐧𝐬𝐨𝐫𝐅𝐥𝐨𝐰, 𝐏𝐲𝐓𝐨𝐫𝐜𝐡, 𝐊𝐞𝐫𝐚𝐬, or 𝐇𝐮𝐠𝐠𝐢𝐧𝐠 𝐅𝐚𝐜𝐞 potentially becoming important depending on the project. Familiarity with data science libraries such as 𝐏𝐚𝐧𝐝𝐚𝐬 and 𝐒𝐜𝐢𝐤𝐢𝐭-𝐥𝐞𝐚𝐫𝐧 is useful because the role involves preparing data and developing analytical solutions rather than working only on theoretical models. The 𝐂𝐎𝐁𝐎𝐋-𝐭𝐨-𝐉𝐚𝐯𝐚 𝐦𝐨𝐝𝐞𝐫𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧 angle is particularly distinctive: it is listed as preferred experience rather than a basic entry requirement, so candidates do not necessarily need legacy-system expertise to be considered. For Indian freshers, the combination of 𝐀𝐈, 𝐝𝐚𝐭𝐚 𝐬𝐜𝐢𝐞𝐧𝐜𝐞, 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐜𝐨𝐧𝐬𝐮𝐥𝐭𝐢𝐧𝐠, and 𝐥𝐞𝐠𝐚𝐜𝐲-𝐜𝐨𝐝𝐞 𝐦𝐨𝐝𝐞𝐫𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧 is less common than the standard Python-plus-ML profile.

Our Take:

- 𝐆𝐨𝐨𝐝 𝐟𝐨𝐫: Candidates with strong 𝐏𝐲𝐭𝐡𝐨𝐧, 𝐦𝐚𝐜𝐡𝐢𝐧𝐞 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠, and data-handling fundamentals who want exposure to enterprise AI projects and are comfortable connecting technical work with business requirements.

- 𝐍𝐨𝐭 𝐢𝐝𝐞𝐚𝐥 𝐟𝐨𝐫: Applicants looking only for pure research-oriented data science or highly specialized deep-learning roles, because this position has a significant 𝐜𝐨𝐧𝐬𝐮𝐥𝐭𝐢𝐧𝐠, 𝐩𝐫𝐨𝐭𝐨𝐭𝐲𝐩𝐢𝐧𝐠, 𝐝𝐨𝐜𝐮𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧, and client-facing dimension.

- 𝐒𝐞𝐥𝐞𝐜𝐭𝐢𝐨𝐧 𝐝𝐢𝐟𝐟𝐢𝐜𝐮𝐥𝐭𝐲: Moderate to high — the bachelor's degree requirement is accessible, but the combination of 𝐩𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠, 𝐀𝐈 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤𝐬, 𝐝𝐚𝐭𝐚 𝐬𝐜𝐢𝐞𝐧𝐜𝐞 𝐥𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬, POC development, and business communication creates a broader technical expectation than many fresher roles.

- 𝐂𝐚𝐫𝐞𝐞𝐫 𝐭𝐫𝐚𝐣𝐞𝐜𝐭𝐨𝐫𝐲: This experience can lead toward 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐬𝐭, 𝐀𝐈/𝐌𝐋 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫, 𝐀𝐩𝐩𝐥𝐢𝐞𝐝 𝐀𝐈 𝐂𝐨𝐧𝐬𝐮𝐥𝐭𝐚𝐧𝐭, 𝐀𝐈 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫, or eventually enterprise AI/technical consulting roles. Experience with AI-assisted modernization could also become useful in organizations working on legacy-system transformation.

𝐂𝐨𝐦𝐩𝐞𝐧𝐬𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐧𝐭𝐞𝐱𝐭: IBM has not disclosed compensation for this particular opening in the supplied posting. A reliable role-specific figure cannot therefore be confirmed, and compensation for data science roles can vary significantly with experience, technical depth, and the level at which the candidate enters the organization.

𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲: A generic machine learning resume may not be enough for this opening. Candidates should showcase at least one project where they built a complete 𝐀𝐈 𝐨𝐫 𝐝𝐚𝐭𝐚 𝐬𝐜𝐢𝐞𝐧𝐜𝐞 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧 from data preparation through model evaluation, and POC-style projects that demonstrate how the technology solves a practical business problem can be particularly relevant. If you have exposure to 𝐉𝐚𝐯𝐚, 𝐂𝐎𝐁𝐎𝐋, 𝐜𝐨𝐝𝐞 𝐦𝐢𝐠𝐫𝐚𝐭𝐢𝐨𝐧, or 𝐆𝐞𝐧 𝐀𝐈 𝐜𝐨𝐝𝐢𝐧𝐠 𝐚𝐬𝐬𝐢𝐬𝐭𝐚𝐧𝐭𝐬, highlight it separately because that combination maps closely to one of the more unusual aspects of this position.

Roles & Responsibilities

The position combines data science, AI prototyping, business problem-solving, and technical communication. Rather than focusing solely on model development, the engineer is expected to help turn AI ideas into demonstrable solutions, work with development teams, document technical decisions, and communicate analytical outcomes to both technical and non-technical stakeholders.

- Develop and validate AI and machine learning proof-of-concepts

- Prepare and analyze data for analytical solutions

- Build and evaluate predictive or prescriptive models

- Work with development teams to refine AI prototypes

- Explore Gen AI-assisted code transformation and modernization use cases

- Support solutions involving COBOL-to-Java code transformation

- Collaborate with scientists, engineers, consultants, and database professionals

- Understand business requirements and select suitable modelling approaches

- Evaluate model and prototype outcomes

- Communicate findings and technical results to different audiences

- Prepare solution documentation, technical guides, and best-practice material

Qualifications & Eligibility

The academic requirement is relatively accessible, with a bachelor's degree being the stated minimum and a master's degree listed as preferred rather than mandatory. However, the technical scope is broader than the basic eligibility suggests, so candidates should expect their practical AI and programming ability to matter considerably.

- Bachelor's Degree

- Master's Degree preferred

- Professional position based in Bangalore

- Ability to work with AI, machine learning, and data science concepts

- Experience or knowledge relevant to proof-of-concept development

Skills Required

Python and machine learning are the most important technical foundations, while AI frameworks, data science libraries, cloud familiarity, and enterprise programming experience can strengthen a candidate's profile.

- Python programming

- Artificial intelligence and machine learning

- TensorFlow, PyTorch, Keras, or Hugging Face

- Scikit-learn

- Pandas

- Matplotlib

- Data preparation and analysis

- Predictive and prescriptive modelling

- Proof-of-concept development

- Familiarity with cloud platforms

- Java and COBOL knowledge is preferred