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Data Scientist - Fraud Modeling - Assistant Vice President

Citigroup

Data Scientist - Fraud Modeling - Assistant Vice President

Citigroup

BANGALORE, Karnātaka, India

·

On-site

·

Full-time

·

2w ago

Developed communication and diplomacy skills are required in order to guide, influence, and convince others, in particular colleagues in other areas. Partner closely and manage interaction with Strategy partners and Model Risk Management validators across the model lifecycle including validation, ongoing performance evaluation, and annual reviews. Responsible for model development, validation and testing of fraud detection models, including statistical analysis, data validation and model performance evaluation using tools like Python, H2O Responsible for documenting data requirements, data collection / processing / cleaning, and exploratory data analysis, which may include utilizing statistical models / algorithms and data visualization technique. Ensure compliance with regulatory requirements and industry best practices in fraud detection and model validation. Identifies and compiles large complex data sets using a variety of tools (e.g. Hive, SQL) to help predict, improve, and measure the success of key business to business outcomes Specialization in fraud or risk domain preferred 8+ years of hands-on analytical experience 5+ years' experience in statistical analysis with working knowledge of at least one of the following statistical software packages: Python (Must), Hive, Spark, SAS Strong quantitative, analytical, and problem-solving skills; knowledge of probability theory, statistics, mathematical finance, econometrics, numerical methods Strong proficiency in statistical analysis and model validation techniques. A solid grasp of traditional and advanced modeling techniques and algorithms, such as Logistic Regression, Gradient Boosting, Random Forests, etc. Expertise in model evaluation techniques such as ROC curves, precision-recall, KS, cross-validation, feature importance, SHAP values, etc. Familiarity with regulatory requirements and guidelines related to risk model validation. Strong communication and interpersonal skills; experience with Stakeholder management Strong project management and organizational skills; ability to multi-task and meet deadlines. Ability to work independently. Risk and control mindset: ability to ask incisive questions, assess materiality and escalate issues. Ability to handle large volumes of transactional data. Familiarity with data extraction tools like Hive will be an advantage. Successful candidate will have a demonstrable analytical problem solving, and the ability to deliver projects in a fast-paced environment. Willing to learn and can-do attitude. Master's/Bachelor's/PhD degree in Statistics, Economics, Finance, Mathematics or a related quantitative field; Engineering/MBA background from a premier institute ------------------------------------------------------ For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------

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About Citigroup

Citigroup

Citigroup

Public

Citigroup 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

35%

Recommend to a Friend

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