Data Analytics Vice President

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Job Overview

The Markets Data Risk team is looking for a Data Analytics VP to support the objectives of reducing the risk of poor data quality across Markets functions.

The scope of the Markets Data Risk programme covers risk management activities across First Line and Second Line functions and the initiative sets out to improve and enhance risk management controls and processes across for all Markets businesses and Citi Treasury Investments (CTI)

The role will be part of a core central Data Analytics project delivery team, charged with ensuring the timely execution of deliverables across multiple workstreams, whilst imparting their subject matter expertise and know-how of Business Data Analytics techniques and delivery. Much of the delivery effort is focused on building durable, long term solutions in partnership with Technology

The candidate must be an individual experienced in Data Analytics, with both hands-on skill and with sufficient domain knowledge to be able to provide meaningful solutions that are functional and sustainable.  The role will directly contribute to a measurable improvement in data quality and consequently a reduction in financial and non-financial risks. The candidate will have the opportunity to join a team of seasoned experts, and accelerate professional growth through unparalleled mentorship and collaborative learning opportunities

Primary Responsibilities

• Support the Data Analytics Lead in the development of a best-in-class Data Analytics platform to provide meaningful insights into the causes of data quality issues so that remediation efforts can be focused to drive Risk Reduction

• Compile insightful, actionable analysis of trends against Data Quality Indicators (Metrics) to support governance forums and decision making by senior management

• Own and design data and feature specifications to leverage Control outputs and work with Technology partners to develop new high-impact report and dashboard analytics

• Plan and co-ordinate UAT activities for new Data Analytics and Metrics integration capabilities

• Identify Risks & Issues and proactively seek to resolve or escalate them in a timely and well-articulated manner

• Be self-starting and enthusiastic, with a proven ability to hit the ground running

• Handle complexity, ambiguity and a fast changing, often demanding work environment

• Drive change to business practices by working effectively across a global organization

• Demonstrate analytical skills with follow-up and problem-solving capability

Key Skills Required

• Relevant experience as a Data Analytics specialist within Banking, preferably Markets

• Comprehensive understanding of all aspects of Data and the role it plays in supporting business decisioning. Knowledge and experience of data modelling (e.g. dimensional data modelling for analytical warehouses) and common patterns of data manipulation are essential.  Experience modelling complex financial instruments and risk data is important

• Understanding of the key data quality themes typically experienced at the touchpoints between processes in large complex technology environments

• Very strong SQL skills with previous experience in solving complex data problems using SQL

• Advanced Tableau skills to support data analysis and develop storytelling through efficient visualisations

• Solid understanding of the Python ecosystem, including the use of Jupyter notebooks to analyse data and how to structure a python application. Must have experience with core python libraries (e.g. Pandas, NumPy)

• Ability to work off own initiative to identify opportunities for improvement and better data insight

• Excellent attention to detail when analysing and documenting data and business requirements

• Proficiency with Excel and PowerPoint

• Ability to manage task level detail in JIRA

• Excellent oral and written communications skills; must be both articulate and persuasive

• Bachelor’s/University degree

Key Skills Preferred

• Good understanding of Control points in Front Office trade booking and valuation processes and their interaction with Market Risk Management and Product Control

• Exposure to python data science methodologies (e.g. encoding) and libraries (e.g. scikit-learn)

• Experience with Apache Airflow