C13-VP-Data Scientist-Fraud Model Development -PUNE

Citi Bank; Pune District; On-site; INR 2,200,000 - 5,200,000; Full time

Job summary

Citi Bank is seeking an energetic Fraud Analytics Sr. Analyst to join its team in Pune, India.

The role focuses on fraud model development, validation, and performance evaluation for card businesses, using Python, Hive and SQL to analyze large data sets. The ideal candidate brings extensive experience in statistical analysis, model evaluation techniques, and a strong ability to communicate with stakeholders across functions.

Qualifications

• 8+ years in hands-on analytics and fraud domain.
• Experience with Python, SQL and data validation.
• Knowledge of model validation and evaluation metrics.

Responsibilities

• Develop, validate and test fraud detection models.
• Collaborate with Strategy partners and Model Risk validators.
• Document data requirements and perform exploratory data analysis.
• Ensure regulatory compliance and best practices in model governance.

Skills

Analytical thinking

Stakeholder management

Tools

Python

Hive

Spark

SQL

H2O

SAS

Job description

About Citi: Citi, the leading global bank, has approximately 200 million customer accounts and does business in more than 160 countries and jurisdictions. Citi provides consumers, corporations, governments and institutions with a broad range of financial products and services, including consumer banking and credit, corporate and investment banking, securities brokerage, transaction services, and wealth management. Our core activities are safeguarding assets, lending money, making payments and accessing the capital markets on behalf of our clients. Citis Mission and Value Proposition explains what we do and Citi Leadership Standards explain how we do it. Our mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. We strive to earn and maintain our clients and the publics trust by constantly adhering to the highest ethical standards and making a positive impact on the communities we serve. Our Leadership Standards is a common set of skills and expected behaviors that illustrate how our employees should work every day to be successful and strengthens our ability to execute against our strategic priorities. Diversity is a key business imperative and a source of strength at Citi. We serve clients from every walk of life, every background and every origin. Our goal is to have our workforce reflect this same diversity at all levels. Citi has made it a priority to foster a culture where the best people want to work, where individuals are promoted based on merit, where we value and demand respect for others and where opportunities to develop to are widely available to all.

Job Description: Citi is looking for an energetic, motivated professional to join its Fraud Analytics team. As part of the Global Fraud Analytics team, this role is responsible for the fraud model development and validation supporting Citis North American Cards business. The Specialized Analytics Sr. Analyst is a strategic professional who closely follows latest trends in own field and adapts them for application within own job and the business. Excellent communication skills required in order to negotiate internally, often at a senior level. Developed communication and diplomacy skills are required in order to guide, influence, and convince others, in particular colleagues in other areas.

Responsibilities

• 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
• 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

• 8+ years of hands-on analytical experience5+ years experience in statistical analysis with working knowledge of at least one of the following statistical software packages: Python (Must), Hive, Spark, SASStrong 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 escalating, managing and reporting control issues with transparency.
• Ability to handle large volumes of transactional data.
• Familiarity with data extraction tools like