Analyst – Data Science (AI/ML)

Oracle's interview process typically spans five rounds: an initial resume screen, an online coding and aptitude test, two technical interviews focusing on ML algorithms, GCP services and product case studies, followed by an HR round. The difficulty is moderate to high, with emphasis on problem‑solving, system design thinking and clear communication. Preparing with GCP labs and product‑management scenarios greatly helps.

Round 1: Resume Screening → Round 2: Online Technical Assessment (Python/SQL coding + aptitude) → Round 3: Technical Interview 1 (ML algorithms, GCP, SQL) → Round 4: Technical Interview 2 (Product case study) → Round 5: HR Interview

Oracle's work culture emphasizes continuous learning, merit‑based growth and a collaborative environment. Employees enjoy a balanced work‑life schedule, access to cutting‑edge cloud technologies and clear career progression pathways.

Undergraduate (B.E/B.Tech/B.Sc) or Post‑graduate (M.E/M.Tech/M.Sc) degree in Computer Science, Information Technology, Mathematics or related fields from a recognized institute. Minimum aggregate of 60% (or CGPA 6.0/10). Freshers from the 2026 batch are eligible. No active backlogs at the time of joining. Candidates must possess strong fundamentals in AI/ML, Python, SQL and GCP.

American Express is a globally integrated payments and financial services company that has built a reputation for data‑driven decision making. With a presence in more than 130 countries, Amex combines cutting‑edge technology with deep financial expertise to deliver products, insights and experiences that enrich lives. The company’s culture emphasizes innovation, collaboration and continuous learning, making it an attractive destination for fresh talent eager to work on real‑world problems at scale.\n\nThe Data Science Analyst role in Bangalore sits at the intersection of technical AI/ML development and product management. As a fresher, you will be part of a high‑impact team that builds end‑to‑end machine‑learning solutions on Google Cloud Platform, while also shaping the long‑term AI product roadmap. This hybrid position offers the chance to write production‑grade code, design experiments, and translate business requirements into scalable AI products.\n\nKey Responsibilities:\n1. Contribute to the definition and articulation of AI product strategy and roadmaps aligned with business metrics.\n2. Prioritize, groom and manage product backlogs using JIRA/Rally.\n3. Design, develop, and validate machine‑learning models from feature engineering to deployment on Vertex AI.\n4. Build proof‑of‑concepts (POCs) for innovative AI/ML solutions with scaling potential.\n5. Collaborate with engineering, UX and data engineering teams to turn MVPs into production‑grade capabilities.\n6. Own the end‑to‑end ML lifecycle, including data ingestion, model training, monitoring and continuous improvement.\n7. Conduct market and competitor research to inform product enhancements.\n8. Document technical designs, experiment results and product specifications in Confluence.\n9. Participate in code reviews and knowledge‑sharing sessions to foster a learning environment.\n10. Communicate findings and product impact to stakeholders across business and technology functions.\n\nTech Stack: Python, SQL, Google Cloud Platform (BigQuery, Vertex AI), PySpark, Hadoop, Jupyter notebooks, Airflow, JIRA, Rally, Confluence, Decision Trees, XGBoost and other ML algorithms.\n\nGrowth Path: Starting as an Analyst – Data Science, high performers can progress to Senior Analyst, AI Product Manager, or Data Science Lead within 2‑3 years, with opportunities to move into broader product or engineering leadership roles.\n\nWhy Join? You will work with a world‑class data science team, gain hands‑on experience with GCP’s AI services, and influence product decisions that affect millions of customers. The role offers a blend of coding depth and strategic product exposure, excellent mentorship, and a compensation package that is among the best in the industry.