Data Science Lead Analyst (VP)

Key Skills

Analytical and Problem solving, Apache Hadoop, ArcGIS, Big Data Technology, Data Engineering, Data Mining, Data science techniques, Database, Java Programming, Leadership, Machine learning techniques, MySQL, Oracle, Python Programming, R Programming, Risk Analytics, SAS, SQL, Teradata

Job Description

At Citi, we are monitoring transactions across traditional and emerging platforms. The Global Data Intelligence & Analytics Team uncovers money laundering, fraud, and other illegal activities by leveraging subject matter expertise, data analysis, advanced algorithms, and behavior-based analytics. We work globally with partners in business, compliance, and investigations to provide best in class experience for our customers while identifying potential risk to the firm.

The ideal candidate is a problem solver, equipped with proven analytical skills suited to approach varied challenges in complex environments. Adept at creative and critical thinking, can deconstruct the problem and transform personal insights into solutions.

As a Data Intelligence & Analytics Lead Data Science Analyst, you will apply your strategic and analytical skills to enterprise wide challenges. You will team with world-class professionals to identify actionable insights that ultimately impact the safety and soundness of the organization. You will work in a space that looks deeply into emerging risk trends and the business enablement opportunities that help fuel strategic decisions.

You will work in a collaborative environment that values your insight, encourages you to take on new responsibilities, promotes continuous learning, and rewards innovation with multi-disciplinary global team with a range of industry experiences and expertise.

Responsibilities:

• The Lead Data Science Analyst must demonstrate critical thinking, analytical and problem-solving abilities, hands-on intelligence led data analysis skills, network analysis acumen, and intellectual curiosity is essential for data science tasks. The candidate must be able to apply these abilities to detect non-obvious risks or develop, test, and champion ideas to increase detection. The candidate should be able to understand machine learning, graph/network theory, predictive modeling, and visualization techniques to leverage internal and external data to identify and develop ways to systemically detect financial crime risk.

Specifically, the candidate should:

• Develop and leverage innovative features and algorithms to drive down false positives and identify perceived threat across the firm
• Demonstrate an ability to apply curiosity and critical thinking and turn data mining, analytics, and derivative outputs / presentations into coherent business driven implementation proposals.
• Utilize traditional statistical analytics, graph theory / network science, ensemble methods and the like Natural language processing, text analytics, factors analysis / construct development and testing, machine learning feature development and engineering, etc.
• Conduct data mining / query functions across relational or big data databases utilizing various data science tools and methods.
• Understand the difference between information and intelligence; demonstrates previously applied research to create intelligence from big data sets and drive decision recommendations
• Supports and/or runs global/regional internal SMEs; responsible for investigating and researching the Financial Crimes processes and tools identifying efficiency and effectiveness opportunities.
• The role requires the ability to develop and effectively communicate recommendations to senior leadership.
• May direct or participate in the development, testing, and training of new or enhanced tactical solutions or strategic system applications.
• Head or participate in the training, development, mentoring of junior employees.
• May be required to participate in Industry/SME Forums as applicable.
• Head in conversation on Law Enforcement requests.

Qualifications:

• 6-10 years’ experience using data science tools and methods
• Exceptional understanding & hands-on across Financial Crime ) AML / Fraud / Cyber / Sanctions / Corruption / Anti-Bribery Risks and Typologies) domain, as well as transaction monitoring processes used to mitigate these risks
• Exceptional research and analytical skills, business acumen, strategic and creative thinking, project leadership skills and multi-tasking capabilities
• Exceptional SQL skills using tools like Teradata, MS SQL, MySQL, Hadoop
• Exceptional skills using tools like: Python, R, SAS or similar statistical package
• Experience with graph theory / network science analysis and tools is a plus.
• Hands-on on various statistical models & possess excellent experience.
• Experience in tools such as Palantir, I2 Analyst Workbook, Semantica, ArcGIS and other domain specific tools is a plus.
• Experience with Oracle is a plus.
• Ability to analyze large sets of complex data, draw meaningful conclusions, and make business recommendations based on analysis
• Ability to handle multiple projects simultaneously in a fast-paced and dynamic financial services environment
• Experience in developing documentation that meets the highest regulatory standards and audit requirements
• Experience in developing reports and updates to senior management regarding the above activities
• Exceptional interpersonal and communication skills, in dealing with people at all levels of the organization both written and verbal.
• Intellectual curiosity, passion for problem-solving, and comfort with ambiguity
• Ability to take initiative and execute against key projects independently
• Ability to thrive in a cross-functional environment while juggling multiple responsibilities
• High energy and a desire to work in a results-oriented, fast growth environment

Preferred Skills:

• Passionate and Committed
• Ability to work with virtual users and a global team located in different hubs.
• Experience with managing an analytical team or transformational task force is a plus
• Ideally, the candidate for this position would demonstrate proficiency in one or more (Citi) lines of business.
• Track record of delivering projects within tight timelines.
• Financial / banking background is a plus.

Education:

Bachelor’s/University degree or equivalent experience, potentially MBA or Advanced Degree in Data Science / Information Systems, Business Analysis / Computer Science.

Master’s or PhD in data analytics / data science