C12-AVP Data Scientist-Fraud Model Development - PUNE

The Specialized Analytics Sr Anlst is a seasoned professional role. Applies in-depth disciplinary knowledge, contributing to the development of new techniques and the improvement of processes and work-flow for the area or function. Integrates subject matter and industry expertise within a defined area. Requires in-depth understanding of how areas collectively integrate within the sub-function as well as coordinate and contribute to the objectives of the function and overall business. Evaluates moderately complex and variable issues with substantial potential impact, where development of an approach/taking of an action involves weighing various alternatives and balancing potentially conflicting situations using multiple sources of information. Requires good analytical skills in order to filter, prioritize and validate potentially complex and dynamic material from multiple sources. Excellent communication and diplomacy skills are required. Regularly assumes informal/formal leadership role within teams. Involved in coaching and training of new recruits. Significant impact in terms of project size, geography, etc. by influencing decisions through advice, counsel and/or facilitating services to others in area of specialization. Work and performance of all teams in the area are directly affected by the performance of the individual.

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.
  • Conduct rigorous validation assessment for fraud model validation; develop and implement validation methodologies to assess model accuracy, robustness, and effectiveness.
  • Ensure compliance with regulatory requirements and industry best practices in fraud detection and model validation.
  • Incumbents work with large and complex data sets (both internal and external data) to evaluate, recommend, and support the implementation of advanced Machine Learning Models.
  • Identifies and compiles 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
  • Responsible for documenting data requirements, data collection / processing / cleaning, and exploratory data analysis, which may include utilizing statistical models / algorithms and data visualization technique.
  • 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 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 understanding of statistical concepts and modelling techniques including traditional and advanced ML algorithms
• 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.

Education:

• Master’s/Bachelor’s/PhD degree in Statistics, Economics, Finance, Mathematics or a related quantitative field; Engineering/MBA background from a premier institute

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

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