Intern (Technology - 3 months)
GB01 - London, United Kingdom
⚠️ We'll shut down after Aug 1st - try foo🦍 for all jobs in tech ⚠️
Applications have closed
Neuberger Berman
Neuberger Berman Group LLC is a private, independent, employee-owned investment management firm. The firm manages equities, fixed income, private equity and hedge fund portfolios for global institutional investors, advisors and high-net-worth...Job Spec –
- Work with the FI Quant team to understand & deliver their requirements
- Help streamline the datasets (understand/document/perform data quality checks/engage with the data team in US/create & maintain data pipelines)
- Support, maintain & enhance existing processes (ensure timeliness of month end reports, etc.)
- Engage with App Support team to troubleshoot issues when needed
- Build apps/dashboards as needed.
- Someone who is keen and willing to learn
- Comes from a computer science background preferably
- Knowledge of Python modules like Pandas/Requests/SQLAlchemy/Plotly/Matplotlib, etc.
- Understanding of either MS SQL Server / Snowflake
- Knowledge of math and statistics is not necessary but useful to have.
- Knowledge Fixed Income will be helpful but not mandatory.
Neuberger Berman is an equal opportunity employer. The Firm and its affiliates do not discriminate in employment because of race, creed, national origin, religion, age, color, sex, marital status, sexual orientation, gender identity, disability, citizenship status or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact onlineaccommodations@nb.com.
Learn about the Applicant Privacy Notice.
Tags: Computer Science Data pipelines Data quality Mathematics Matplotlib MS SQL Pandas Pipelines Plotly Privacy Python Snowflake SQL Statistics
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.