Senior Data Scientist Assistant Vice President

Citigroup; Tampa (FL); On-site; USD 95,000 - 150,000; Full time

Job summary

Citigroup is seeking an AML Data Scientist to support multiple AML risk projects. You will apply quantitative methods, prepare data for visualization, and build predictive ML models under supervision. Strong communication and team collaboration are required to translate complex analyses for stakeholders.

Responsibilities include data validation, documentation, and automated data workflows. You will operate in a dynamic AML environment, contributing to monitoring optimization and policy-compliant

Qualifications

• Bachelor's degree in statistics, math, data science, or related field.
• Master's degree preferred.
• Experience with AML or financial services is advantageous.
• Strong data manipulation and analysis skills.

Responsibilities

• Apply quantitative and qualitative data analysis methods including Python and SQL to extract, transform and analyze data.
• Prepare statistical and non-statistical data for visualization and exploration, validate data, identify data quality issues in AML risk related projects.
• Contribute towards AML optimization techniques and related deliverables; document optimization solutions and present results to non-technical audiences.
• Build machine learning models (predictive modeling/classification/regression)
• Conduct data analysis, data mining, and create formal statistical documentation; work with technology and sponsors to address issues.
• Analyze and interpret data reports; make recommendations addressing business needs.
• Validate assumptions, escalate risks and sensitive areas in methodology and process.
• Automate recurring data extraction and preprocessing tasks; perform ad-hoc analyses and provide documentation.
• Assess risk when business decisions are made, ensuring compliance with laws and policy.

Skills

Python

SQL

Statistics

Data analysis

Machine learning

Data visualization

Communication

Teamwork

Ethical judgment

Education

Bachelor's in Statistics/Math/Data Science

Masters preferred

Tools

MS Office

Job description

The AML Data Scientist will work under the supervision of a Functional Team Manager to provide ongoing support in terms of required analysis. The scope of analysis will cover all aspects of analysis performed by the team within different projects: Key Performance Indicator Driven Tuning and Tactical Tuning tasks, and data modeling/validation efforts depending on current needs and project plans. The Data Scientist will follow the globally consistent methodology but is expected to have a high level of initiative and creativity and suggest enhancements to current methodologies. The analyst evaluates moderately complex and variable issues with substantial potential impact, where development of an approach/taking an action involves weighing various alternatives and balancing potentially conflicting situations using multiple sources of information. It requires good analytical skills to filter, prioritize and validate potentially complex and dynamic material from multiple sources. Strong communication skills are required. Work and performance of all teams in the area are directly affected by the performance of the individual.

Responsibilities

• Apply quantitative and qualitative data analysis methods including Python (and R), SQL to extract, transform and analyze data.
• Prepare statistical and non-statistical data for visualization and exploration, validate data, identify data quality issues in AML risk related projects.
• Contribute towards AML Optimization techniques and related deliverables i.e. Optimizing monitoring systems, document optimization solutions, and present results to non-technical audiences; write formal documentation using statistical vocabulary.
• Build Machine Learning (Predictive Modeling/ Classification/ Regression) models.
• Conduct data analysis, data mining, read and create formal statistical documentation, and work with Technology and Sponsors to address issues.
• Analyze and interpret data reports, make recommendations addressing business needs.
• Validate assumptions, escalation identified risks and sensitive areas in methodology and process.
• Automate recurring data extraction and data pre-processing tasks, perform ad-hoc data analyses, and provide documentation and presentations.
• Appropriately assess risk when business decisions are made keeping in mind the firm's reputation by being compliant with applicable laws, rules and regulations and adhering to Policy.
• Apply sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, manage and report control issues with transparency.

Qualifications

• Strong statistical/ data science related academic background, knowledge of quantitative methods, including predictive modeling techniques and including both calculation and interpretation of outcome.
• Experience in creating and assessing Statistical Models.
• Good working knowledge of Python, SQL & MS Office Suite.
• Experience in reporting the results of analysis in clear written form, and in presenting the findings during meetings and conference calls.
• Team working experience (demonstrated team player ability required).
• Understanding of technical requirements, ability to communicate with Technical Support.
• Ability to manipulate data using SQL or equivalent.

Desirable

• Experience with data exploration.
• Mantas and AML monitoring systems experience or other transaction monitoring systems a plus.
• Knowledge of the local/regional laws and regulations applicable to anti-money laundering a plus.
• Previous experience with financial services companies (retail banking, small business banking, commercial, institutional, private banking).
• Knowledge of any programming language or dedicated statistical software would be an advantage.

Skills

• Initiative, creativity and attention to detail are essential.
• Ability to work under close supervision of a functional team manager, while preserving independence of thinking and responsibility for the results.
• Ability to discuss reasoning, critical assessment of facts and opinions; ability of giving comprehensive answers and arguments.
• Conceptual and creative thinking (outside the box).
• Demonstrated ability to communicate effectively, both orally and in writing, through all levels of the organization and through different business units.
• Self-motivated with high desire of self-development and learning.
• Must be able to coordinate and deal with conflicting time demands.
• Ability to work non-standard business hours, including weekends and holidays as determined by the business needs. Flexibility will be expected.

Education

• Bachelors (4 Year University) Degree in Statistics, Mathematics, Data Science, Data Analytics, Business Analytics, or related quantitative fields required.
• Masters Degree preferred.

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