Data Scientist, Citi

Citi

Location:
India, Pune

Category:
Banking

Contract Type:
Employment contract

Salary:

Not provided

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Job Description:

Citi is looking for an energetic, motivated professional to join its Fraud Analytics team. The role involves fraud model development and validation supporting Citi’s North American Cards business. The professional is expected to balance technical expertise with strong communication and project management skills.

Job Responsibility:

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
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.

Requirements:

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.

Nice to have:

Specialization in fraud or risk domain
Familiarity with data extraction tools like Hive.

What we offer:

Equal opportunity employer practices promoting diversity
Development opportunities
Best-in-class benefits for wellness and savings.

Additional Information:

Job Posted:
June 07, 2025

Employment Type:

Fulltime

Work Type:

Hybrid work

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Data Scientist