채용
Required Skills
Python
Pyspark
Statistical modeling
Data governance
Data analysis
SQL
The Data Analytics Lead Analyst is a strategic professional who stays abreast of developments within own field and contributes to directional strategy by considering their application in own job and the business. Recognized technical authority for an area within the business. Requires basic commercial awareness. There are typically multiple people within the business that provide the same level of subject matter expertise. 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. Significant impact on the area through complex deliverables. Provides advice and counsel related to the technology or operations of the business. Work impacts an entire area, which eventually affects the overall performance and effectiveness of the sub-function/job family.
Responsibilities:
- Integrates subject matter and industry expertise within a defined area.
- Contributes to data analytics standards around which others will operate.
- Applies in-depth understanding of how data analytics collectively integrate within the sub-function as well as coordinate and contribute to the objectives of the entire function.
- Employs 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.
- Resolves occasionally complex and highly variable issues.
- Produces detailed analysis of issues where the best course of action is not evident from the information available, but actions must be recommended/ taken.
- Responsible for volume, quality, timeliness and delivery of data science projects along with short-term planning resource planning.
- Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.
Qualifications:
- 12 - 15 years experience using codes for statistical modeling of large data sets
- Strategic Data Analysis: Lead complex Bigdata analysis initiatives to identify patterns, anomalies, and opportunities for process improvement within the KYC lifecycle. Should also have strong experience on Python, Pyspark along with data governance
- Insight Generation: Analyze large-scale customer and transactional datasets to generate actionable insights that enhance risk assessment models, improve operational efficiency, and strengthen compliance controls.
- Stakeholder Collaboration: Partner with senior stakeholders across Compliance, Technology, and Operations to understand business challenges, define analytical requirements, and present data-driven recommendations.
- Data-Driven Strategy: Play a key role in defining the data strategy for the KYC modernization program, including data sourcing, quality standards, and governance frameworks.
- Metrics & Reporting: Design, develop, and maintain advanced dashboards and reports to monitor Key Performance Indicators (KPIs) and Key Risk Indicators (KRIs). Provide regular updates to senior leadership on the effectiveness of KYC processes and the progress of the modernization project.
- Data Quality & Governance: Establish and oversee data quality frameworks to ensure the accuracy, completeness, and integrity of KYC data. Lead efforts to remediate data quality issues at their source.
- Advanced Analytics: Utilize statistical techniques and advanced analytical methodologies to develop predictive models for customer risk segmentation and to identify emerging financial crime typologies.
- Mentorship: Act as a subject matter expert and mentor for junior analysts, fostering a culture of analytical excellence and continuous learning within the team.
Education:
- Bachelor’s/University degree or equivalent experience, potentially Masters degree
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
Job Family Group:
Technology
Job Family:
Data Analytics
Time Type:
Full time
Most Relevant Skills
Please see the requirements listed above.
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
*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 *Accessibility at Citi.
View Citi’s EEO Policy Statement and the Know Your Rights poster.
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About Citigroup

Citigroup
PublicCitigroup Inc. or Citi is an American multinational investment bank and financial services company based in New York City. The company was formed in 1998 by the merger of Citicorp, the bank holding company for Citibank, and Travelers; Travelers was spun off from the company in 2002.
10,001+
Employees
New York City
Headquarters
Reviews
3.3
4 reviews
Work Life Balance
3.0
Compensation
3.2
Culture
2.8
Career
2.5
Management
2.7
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Pros
Compensation increases for investment banking roles
Legitimate investment banking employer
Internship opportunities available
Cons
Unclear career progression paths
Limited meaningful experience in internships
Compensation raises lower than competitors
Salary Ranges
28 data points
Mid/L4
Senior/L5
Staff/L6
Mid/L4 · Business Risk Intermediate Analyst
1 reports
$77,165
total / year
Base
$67,100
Stock
-
Bonus
-
$77,165
$77,165
Interview Experience
5 interviews
Difficulty
2.8
/ 5
Duration
14-28 weeks
Experience
Positive 0%
Neutral 40%
Negative 60%
Interview Process
1
Application Review
2
Recruiter Screen
3
Programming Assessment
4
Hiring Manager Interview
5
Panel/Superday Interviews
6
Final Decision
Common Questions
Technical Knowledge
Case Study
Behavioral/STAR
Past Experience
Culture Fit
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