Core Skills and Experience:
5 - 8 years of experience in analytics, data, or quantitative roles within financial services.
Exposure to asset management, private markets, or capital markets (preferred but not mandatory).
Solid SQL skills with experience working on large and complex datasets.
Proficiency in Python / PySpark or willingness to build expertise in programming.
Experience in data modelling for analytics or reporting use cases.
Hands-on experience with BI/visualization tools (Power BI, Tableau, Looker, etc.).
Robust analytical thinking, problem-solving ability, and attention to detail.
Ability to work in a rapid-paced environment and manage multiple priorities.
Knowledge of data governance, controls, and metadata management.
Preferred (but not essential) experience:
Experience working with Databricks, Snowflake, or similar cloud data platforms.
Understanding of data pipelines, ETL processes, or lakehouse architectures.
Knowledge in coding best practices, testing, version control, and automating recurring analytics processes
Experience with building light tools and applications using SQL, Python (eg. Streamlit)
Exposure to private markets datasets or fund analytics.
Prior experience mentoring or leading small teams.