Experian
global data and technology
SeniorDataModelingAnalyst
Neural analysis suggests this role is
optimal for mid candidates.
“Senior Data Modeling Analyst at Experian. Skills: Data Modeling, Statistical Modeling, Machine Learning, SQL, Python, PySpark, AWS. Independently deliver analytical projects across the consumer credit lifecycle, including acquisition, account management and collections. Build statistical and machine learning models through all phases of development, from design through training, evaluation, validation and implementation”
Industry & Context.
Experience solving complex and unique problems; Interpret results of analyses, identify trends and issues and recommend alternatives to support our goals.
What They're Looking For.
Must Have
Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, or a related quantitative field, 8+ years' experience with statistical and quantitative analysis, Machine Learning, Statistical Modeling including large-scale data manipulation in Credit Lending industry, Proficiency in Python (required) and SQL, with experience building scalable pipelines, Knowledge of statistical models and practical experience in predictive model development (Python, R, SAS), Domain experience in financial services, with exposure to credit lending, credit risk modeling, and credit decisioning lifecycle (e. g. , origination, underwriting, limit setting, portfolio monitoring), Experience with model deployment and productionization, including CI/CD pipelines, version control, and integration of models into scalable, real-time or batch decisioning systems, Experience joining large datasets from multiple data sources, creating complex logic for data cleaning, outlier detecting, and refining business rules to validate and monitor the model forecast, Experience solving complex and unique problems
Nice to Have
GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, dbt Certified
What You'll Do.
Independently deliver analytical projects across the consumer credit lifecycle
including acquisition
account management and collections
Build statistical and machine learning models through all phases of development
from design through training
validation and implementation
Use a broad set of technologies: SQL
AWS and more to obtain insights from large volumes of data
Design and improve acquisition strategies
including segmentation
and cut-off strategies
Translate findings into applicable business recommendations for partners
Collaborate with internal and external clients to determine the appropriate analysis parameters and performance measures to be applied
as well as requirements for decision tool and strategy implementation and monitoring.
Interpret results of analyses
identify trends and issues and recommend alternatives to support our goals.
Communicate with and deliver presentations to end-users on analysis results.
Produce implementation plans and participate in audits to help implement statistical models and other decision tools.
Help develop analytic and data products and services
and the enhancement of current processes and offerings.
How You'll Work.
Team & Collaboration
Collaborate with internal and external clients
Communication Scope
Communicate with and deliver presentations to end-users on analysis results
Process & Methodology
Produce implementation plans
Full Job Description
Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries. You'll have opportunity to: * Independently deliver analytical projects across the consumer credit lifecycle, including acquisition, account management and collections * Build statistical and machine learning models through all phases of development, from design through training, evaluation, validation and implementation * Use a broad set of technologies: SQL, PySpark, Python, AWS and more to obtain insights from large volumes of data * Design and improve acquisition strategies, including segmentation, decision rules, and cut-off strategies * Translate findings into applicable business recommendations for partners * Collaborate with internal and external clients to determine the appropriate analysis parameters and performance measures to be applied, as well as requirements for decision tool and strategy implementation and monitoring. * Interpret results of analyses, identify trends and issues and recommend alternatives to support our goals. * Communicate with and deliver presentations to end-users on analysis results. * Produce implementation plans and participate in audits to help implement statistical models and other decision tools. * Help develop analytic and data products and services, and the enhancement of current processes and offerings. ## Qualifications * Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, or a related quantitative field * 8+ years' experience with statistical and quantitative analysis, Machine Learning, Statistical Modeling including large-scale data manipulation in Credit Lending industry * Proficiency in Python (required) and SQ
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