Model Analytics Validation Senior Analyst Assistant Vice President

Citigroup; Tampa (FL); On-site; USD 90,000 - 120,000; Full time

Job summary

Citigroup in the United States seeks a Data Analytics Senior Analyst to apply strategic analytics to enterprise-wide challenges, identifying actionable insights that impact the safety and soundness of the organization. You will work with world-class professionals to detect financial crime risk using machine learning, graph theory, and visualization techniques.

The role emphasizes turning data into intelligence, presenting recommendations to senior leadership, and collaborating across global

Qualifications

• 2-6 years' experience using data science tools and methods.
• Must have SQL query development expertise using tools like Teradata, MS SQL, MySQL, Hadoop.
• Must have data analysis experience using tools like: Python, R or similar statistical package.
• Exceptional research and analytical skills, business acumen, strategic and creative thinking, project leadership skills and multi-tasking capabilities.

Responsibilities

• The Data Analytics Senior 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 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.
• Develop advanced analytical SQL query and functions from scratch across relational and big data databases.
• Develop scripts and codes from scratch and ability to utilize various data science tools and methods using (Python, R etc.)
• Design, automate & implement Tableau dashboards to capture monthly metrics and derive actionable insights
• Develop and leverage innovative features and algorithms to drive down false positives and identify perceived threat across the firm
• Understand the difference between information and intelligence; demonstrates previously applied research to create intelligence from big data sets and drive decision recommendations.

Job description

Our people make all the difference in our success.

At Citi, we are monitoring transactions across traditional and emerging platforms. The AML Global Data 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 risks 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 Analytics Senior 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 Data Analytics Senior 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 advanced analytical SQL query and functions from scratch across relational and big data databases.
  • Develop scripts and codes from scratch and ability to utilize various data science tools and methods using (Python, R etc.)
  • Design, automate & implement Tableau dashboards to capture monthly metrics and derive actionable insights
  • 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.
• May be required to participate in Industry/SME Forums as applicable.

Qualifications:

• 2-6 years' experience using data science tools and methods
• Must have SQL query development expertise using tools like Teradata, MS SQL, MySQL, Hadoop
• Must have data analysis experience using tools like: Python, R or similar statistical package
• Exceptional research and analytical skills, business acumen, strategic and creative thinking, project leadership skills and multi-tasking capabilities
• Experience with graph theory / network science analysis and tools is a plus.
• Hands‑on on various statistical models & possess excellent experience.
• Experience with Oracle is a plus.
• Prior understanding of AI and practically utilizing AI to simplify processes, enhance AI adoption to improve accuracy & efficiency of the tasks performed 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 regu