Company Name:-
Citi

Job Location:-
Mumbai, Maharashtra

Job Summary:-
About Citi Markets:
Citi’s equities business is one of the largest and most established, both regionally and globally.

Our clients include the world’s leading institutional investors and high net worth individuals and we provide these clients with value-added, independent, insightful and actionable investment advice.

The successful candidate will join Citi’s Global Markets Center in Mumbai and will work closely with New York, London and Hong Kong based sales traders, quantitative analysts and technologists.

Job Description:
Position Title: Assistant Vice President – Cash Equities Quant
Business Group: Institutional Clients Group
Grade/Level: Assistant Vice President
Function/Group: Citi Markets
Location: Mumbai
Percentage of Travel: Yes, 10% of the Time
Individual Contributor (IC)/Managerial: IC
Role and Responsibilities:
Day-to-Day Responsibilities:
Citi is looking to expand its team of highly talented individuals who are working on the research and development of analytics, signals and trading tools used in the context of Citi’s cash equities trading businesses.

The work covers a number of product lines including pre-trade, intra-trade, post-trade products, electronic execution and central risk platforms across all major global markets.

A successful candidate will have a demonstrated ability in building quantitative analytics tools with preference given to those with direct experience in market impact cost modeling, algo/signals research or automated management of portfolio risk and a working knowledge of equites market microstructure (or other asset class).

The candidate will use their knowledge of statistics to design, implement and validate models.

They will use their strong programming capability to collect, manipulate and aggregate large data sets and develop production ready components.

They will use their presentation skills to summarize model outcomes and write up compelling analytical notes for internal desks and external clients.

Data types that the team works with include ultra-high frequency market trade and quote (TAQ) data and electronic trading order and execution data.

This data is used to develop:
Algorithmic trading analytics
Microstructure/signals research
Pre-trade cost and risk estimates

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