Data Analyst

UBS typically conducts a three‑stage interview process: an online aptitude test, followed by a technical interview focusing on SQL, Python, and data concepts, and finally an HR round assessing cultural fit and communication. The difficulty is moderate, with emphasis on logical reasoning and practical data‑handling knowledge. Preparing with real‑world data scenarios and clear articulation of past projects helps candidates stand out.

UBS promotes a collaborative and inclusive work environment where learning and mentorship are emphasized. Employees enjoy a balance between challenging projects and supportive team dynamics, with clear pathways for career progression and skill development.

Graduates (B.Tech/B.E., B.Sc., B.Com, or MBA) in Computer Science, Statistics, Finance, Economics or related fields; minimum 60% aggregate or CGPA 6.5/10; batch 2024/2025; no active backlogs (max 2 allowed at time of joining); strong analytical mindset and good communication skills.

Round 1: Online aptitude test (quantitative, logical reasoning, verbal) → Round 2: Technical interview (SQL, Python, data concepts) → Round 3: HR interview (behavioral, fit, motivation)

UBS is one of the world’s largest and most respected financial services firms, headquartered in Zurich, Switzerland. With a presence in over 50 markets, UBS offers a broad range of services including wealth management, investment banking, and asset management. In India, UBS has been expanding its footprint, especially in the technology and data domains, to support its global operations. The firm is known for its strong emphasis on innovation, compliance, and client‑centric solutions, making it an attractive employer for fresh talent looking to build a career in finance and technology. The Data Analyst role in the Asset Management division is positioned at the intersection of business and technology. The analyst will join the Data Services Operations team in Pune, which is responsible for delivering accurate security reference, price, analytics, and benchmark data to the broader UBS Asset Management business. The team works across multiple time zones, providing 24*6 coverage, and collaborates with colleagues in Chicago, Krakow, Zurich, and Singapore. This role offers a unique opportunity to understand the end‑to‑end data lifecycle in a global asset management environment, from data ingestion to delivery, while contributing to process automation and quality improvement initiatives. Key responsibilities include: 1. Oversee day‑to‑day BAU delivery across multiple data services teams to ensure operational stability. 2. Drive continuous process improvements and document best practices. 3. Act as the primary escalation point for data quality and process issues with internal stakeholders and external data providers. 4. Track, report, and mitigate risks, monitoring key performance indicators (KPIs) and non‑functional requirements (NFRs). 5. Lead and coordinate multiple projects, ensuring timely delivery and stakeholder alignment. 6. Collaborate with IT, data vendors, and global teams to design and implement data solutions. 7. Identify automation opportunities to reduce manual effort and improve efficiency. 8. Contribute subject‑matter expertise to division‑wide data initiatives and governance forums. 9. Proactively anticipate potential problems and implement preventive measures. 10. Follow established escalation guidelines and ensure timely communication of issues. 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. Knowledge of data quality tools, ETL processes, and version control (Git) is advantageous. UBS offers a clear growth path: analysts can progress to senior analyst, data engineer, or product owner roles, with opportunities to move across geographies or into specialized asset‑management functions. Why join UBS? The firm provides a global platform, robust training programs, and a collaborative culture that values diversity and inclusion. Freshers gain exposure to real‑world financial data, cutting‑edge technology, and mentorship from seasoned professionals, positioning them for a rewarding long‑term career in finance and analytics.