Data Analyst

UBS interview experience typically consists of an online aptitude test followed by a technical interview focusing on SQL queries, data manipulation and basic programming concepts. The final HR round assesses cultural fit, communication skills and motivation. Preparation should include mock tests, data‑related case studies and clear articulation of past project experiences.

UBS promotes a collaborative and inclusive culture where employees are encouraged to share ideas and drive innovation. The firm offers structured growth programs, mentorship and a healthy work‑life balance, especially for roles with global coverage.

Graduates (B.Tech, B.E., B.Sc., MCA, or equivalent) from any stream with a minimum of 60% aggregate (or 6.0 CGPA). Freshers graduating in 2024‑2025 are preferred. No active backlogs at the time of joining. Strong analytical mindset, good communication skills and willingness to work in a global, cross‑cultural environment.

Round 1: Online Aptitude & Logical Reasoning Test → Round 2: Technical Interview (SQL, Python, Data Concepts) → Round 3: HR Interview (fitment, motivations, cultural fit)

UBS is one of the world’s largest and most respected financial institutions, headquartered in Zurich with a presence in over 50 markets. In India, UBS has built a strong foothold across wealth management, investment banking and asset management, offering a collaborative environment that blends global best practices with local expertise. The firm prides itself on a culture of integrity, innovation and inclusion, encouraging employees to grow through continuous learning and exposure to cutting‑edge financial technologies. The Data Analyst role in the Asset Management Data Services team is positioned at the heart of UBS’s data‑driven decision making. As a Data Services Operations Lead, you will be responsible for ensuring the seamless delivery of security reference, price, analytics, index and benchmark data to internal stakeholders. You will work closely with cross‑functional teams across Chicago, Krakow, Zurich, Singapore and Pune, acting as a bridge between data service leads and business users while maintaining high data quality and operational stability. Key responsibilities include: 1. Oversee BAU delivery across multiple data teams, ensuring 24×6 coverage and minimal downtime. 2. Lead escalation management for data and process issues, coordinating with IT, data providers and global stakeholders. 3. Drive continuous process improvements and automation initiatives to reduce manual effort. 4. Track, report and mitigate risks, including non‑functional requirements and KPI deviations. 5. Manage multiple projects simultaneously, ensuring timely delivery and stakeholder alignment. 6. Identify and implement opportunities to streamline data management workflows. 7. Contribute subject‑matter expertise to division‑wide and group‑wide data initiatives. 8. Maintain documentation, SOPs and governance standards for data services. 9. Mentor junior analysts and foster a culture of accountability and collaboration. 10. Ensure compliance with regulatory and internal risk policies. The tech stack typically includes SQL, Python/R for data manipulation, Tableau/PowerBI for visualization, and exposure to cloud platforms such as AWS or Azure. Familiarity with data quality tools, ETL pipelines and AI‑enabled workflow automation is advantageous. Growth path: Starting as a Data Analyst, high performers can progress to Senior Analyst, Data Services Manager, and eventually to leadership roles such as Head of Data Operations or Chief Data Officer within the Asset Management division. UBS invests heavily in upskilling through internal training, certifications and mentorship programs. Why join UBS? You will be part of a global powerhouse that values innovation, offers exposure to sophisticated financial instruments, and provides a supportive environment for career acceleration. The role offers a blend of technical challenges and business impact, making it an ideal launchpad for ambitious freshers seeking a long‑term career in finance and data analytics.