Data Scientist-Artificial Intelligence

IBM’s interview process typically starts with an online coding test focusing on Python and SQL, followed by a technical interview that probes machine‑learning fundamentals, model‑building experience and POC discussions. The final HR round assesses cultural fit and communication skills. Candidates should practice data‑science case studies and be ready to discuss real‑world AI projects.

IBM promotes a collaborative, innovation‑driven culture where employees are encouraged to experiment and learn continuously. The company offers structured career development programs, mentorship and a balanced hybrid work model that supports both personal well‑being and professional growth.

Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics or related field (Master's preferred). Minimum 60% aggregate (or CGPA 6.0/10). No active backlogs at the time of joining. Graduation batch 2023‑2026 accepted. Strong analytical mindset and passion for AI/ML required.

Round 1: Online coding assessment (Python/SQL) → Round 2: Technical interview (ML concepts, case studies, POC discussion) → Round 3: HR interview (fit, motivation, cultural alignment)

IBM (International Business Machines) is a global technology and consulting powerhouse that has been shaping the IT landscape for over a century. With a presence in more than 170 countries, IBM offers end‑to‑end solutions across cloud, AI, quantum computing, blockchain and enterprise services. The company’s consulting arm, IBM Consulting, partners with Fortune‑500 firms to drive digital transformation, leveraging hybrid cloud platforms and cutting‑edge artificial intelligence. IBM’s culture emphasizes continuous learning, diversity, and responsible innovation, making it a preferred destination for technologists who want to work on large‑scale, impact‑driven projects. The role of Associate Data Scientist – Artificial Intelligence is positioned within IBM Consulting’s Data & Analytics practice. As an entry‑level data scientist, you will collaborate with senior consultants, engineers and domain experts to turn raw data into actionable insights for clients across industries such as banking, healthcare, retail and manufacturing. You will be responsible for building, validating and deploying predictive and prescriptive models that help clients anticipate market trends, optimise operations and enhance customer experiences. The position offers exposure to IBM’s AI application suites, Red Hat’s open‑source tools and the broader IBM Cloud ecosystem. **Key Responsibilities** 1. Design, develop and validate predictive and prescriptive machine‑learning models using Python, R and AI frameworks (TensorFlow, PyTorch, Keras, Hugging Face). 2. Cleanse, transform and integrate large‑scale datasets, ensuring reproducibility and efficiency. 3. Create and maintain statistical models that handle big‑data environments and support real‑time analytics. 4. Build Proof‑of‑Concept (POC) solutions to demonstrate feasibility of AI use‑cases for clients. 5. Collaborate in Agile squads with data engineers, solution architects and business analysts to deliver end‑to‑end analytics pipelines. 6. Document solution architecture, design decisions and best‑practice guidelines for internal and client consumption. 7. Communicate findings and model outcomes to both technical and non‑technical stakeholders through visualisations and clear narratives. 8. Participate in code‑refactoring POCs, especially translating legacy COBOL logic to modern Java implementations using Gen AI assistants. 9. Stay updated with emerging AI research and contribute ideas for new service offerings. 10. Support knowledge‑sharing sessions and mentor junior team members as you grow. **Tech Stack**: Python, R, TensorFlow, PyTorch, Keras, Hugging Face, Scikit‑learn, Pandas, NumPy, Matplotlib, SQL, IBM Cloud, Red Hat OpenShift, COBOL, Java, Git, Docker, Agile tools. **Growth Path**: Starting as an Associate Data Scientist, you can progress to Data Scientist, Senior Data Scientist, AI Solution Architect and eventually to leadership roles such as AI Practice Lead or Consulting Manager. IBM invests heavily in internal up‑skilling through digital badges, certifications and mentorship programs. **Why Join IBM?** IBM offers a globally recognised brand, access to world‑class AI platforms, and the chance to work on transformative projects for industry leaders. The hybrid work model provides flexibility while fostering collaboration. Employees benefit from robust learning resources, a diverse inclusive environment and a clear career ladder that rewards technical excellence and client impact.