Specialized Analytics Manager (Fraud Intelligence), VP - Hybrid

TN United Kingdom
London
1 week ago
Create job alert

Social network you want to login/join with:

col-narrow-left

Client:

00002 Citibank, N.A.

Location:

London, United Kingdom

Job Category:

Other

-

EU work permit required:

Yes

Job Reference:

ae7e627bc7a8

Job Views:

101

Posted:

14.03.2025

Expiry Date:

28.04.2025

Job Description:

The Specialized Analytics Sr. Mgr accomplishes results through the management of professional team(s) and department(s). Integrates subject matter and industry expertise within a defined area. Contributes to standards around which others will operate. Requires in-depth understanding of how areas collectively integrate within the sub-function as well as coordinate and contribute to the objectives of the entire function. Requires basic commercial awareness. Developed communication and diplomacy skills are required in order to guide, influence and convince others, in particular colleagues in other areas and occasional external customers. Has responsibility for volume, quality, timeliness and delivery of end results of an area. May have responsibility for planning, budgeting and policy formulation within area of expertise. Involved in short-term planning resource planning. The team is Internal Fraud Intelligence that focuses on conducting data analysis to identify fraud risk and trends, fraud scenario design and optimization, analytical process and data quality management, stakeholder management and reporting.


Responsibilities:

  1. Lead internal fraud analytics in NAM, engage and collaborate with business, fraud and control stakeholders, use advanced analytics to proactively identify fraud risk and trends.
  2. Own the knowledge and quality of internal fraud detection data in NAM. Collaborate with technology to implement the right analytics platform, data structure, pipeline and transformation in Citi Bigdata ecosystem.
  3. Extract knowledge and insights from data in order to design complex internal fraud detection solution through a range of data preparation, modeling, and visualization techniques, including predictive analysis, pattern recognition and Machine Learning. Key skills include association rule learning, cluster analysis, anomaly detection, data analysis and visualization (PowerBI, Qlik, Tableau), object-oriented programming (Python, Spark, SAS).
  4. Be the regional analytics point person for stakeholder management and communication, including regional assurance review such as Internal/ External Audit review, Compliance Assurance review.
  5. Support Internal Fraud Governance team to design and execute analytical process such as change management.


Qualifications:

  1. Bachelor's Degree required in statistics, mathematics, physics, economics, or other analytical or quantitative discipline. Master's Degree or PhD preferred.
  2. 5-8 years of experience in data analytics, modeling and analytical project implementation.
  3. Experience working with Big Data environment with hands on coding experience within various traditional (SAS, SQL, etc.) and/or open source (Python, Impala, Hive, etc.) tools.
  4. Traditional and advanced machine learning techniques and algorithms, such as Logistic Regression, Gradient Boosting, Random Forests, etc.
  5. Data visualization tools, such as Tableau.
  6. Excellent quantitative and analytic skills; ability to derive patterns, trends and insights, and perform risk/reward tradeoff analysis.
  7. Good written and verbal communication skills, with ability to connect analytics to business impacts; comfortable presenting to peers and management.
  8. Extremely detail-oriented; intellectual curiosity.
  9. Provide analytic thought leadership.
  10. Manage project planning effectively.
  11. Deep understanding of data management such as data pipeline and data quality; Stakeholder management including internal audit, regulators.

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

* Must have flexibility to attend meetings outside of normal business hours.


Job Family Group:Decision Management


Job Family:Specialized Analytics (Data Science/Computational Statistics)


Time Type:Full time


Primary Location:Jacksonville Florida United States


Primary Location Full Time Salary Range:$125, - $188,


In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit Available offerings may vary by jurisdiction, job level, and date of hire.


Anticipated Posting Close Date:Jun 18, 2024


Citi is an equal opportunity and affirmative action employer. Qualified applicants will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Citigroup Inc. and its subsidiaries ("Citi”) invite all qualified interested applicants to apply for career opportunities. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review.

#J-18808-Ljbffr

Related Jobs

View all jobs

Power & Gas Trading Risk Manager

Security Manager, Traffic Quality Forensics

Senior Customer Experience Program Manager - Azure Data Engineering

Quantitative Researcher - Equity Volatility

Data Strategy & Governance Lead

Technical Project Manager

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.