Founder/Chief Consultant at Credence HR Services
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Vice President - Fraud Analytics - Data Scientist (8-11 yrs)
We have the following role with our client in Mumbai
Success in this role requires a strong foundation in predictive modeling and machine learning coupled with proven ability to deploy scalable solutions that can handle a massive amount of data and computation. Expert communication and collaboration skills are also required. Your key responsibilities will include:
Feature selection for traditional GLM models (e.g Lasso, ElasticNet, etc) and machine learning models
Machine Learning Algorithm Development
Retooling/enhancing existing machine learning algorithms
Implementing new machine learning algorithms that are available from the public domain
Fraud Detection Model Development
Collaborate with fraud prevention/detection strategy teams and operations to understand business needs, data generating process, system capability, and potential impact of models.
Design machine learning algorithms that can be used to improve the fraud prevention/detection scores
Source data and apply feature engineering for model development and deployment
Provide requirements and assist Information Technology for model deployment
Document model solutions and address questions/concerns from model risk and control partners
PhD./ Master's degree in Mathematics, Statistics, Economics, Computer Science, or related fields
Expert in generalized linear models, unsupervised and supervised machine learning algorithms
Demonstrated experience with Big Data tools like Hadoop & Spark
Demonstrated proficiency in advanced analytical languages such as R, Python, Scala, SAS
Experience with traditional database/system languages (e.g. SAS, SQL, etc.) to collaborate with other data analysts/systems
Experience with implementing scalable machine learning/data mining algorithms making use of distributed/parallel processing
Minimum 10 years of experience in Model development for Financial Services.
Please feel free to write to me expressing your interest in exploring the role.
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