Atlanticus
Overview
Title: Senior Data Scientist Location: Atlanta, GA or Austin, TX — Hybrid (3 days onsite, 2 days remote) Team Overview Atlanticus is looking for an experienced and passionate senior data scientist in our Risk Management team. This role will partner with collections, operations, marketing and other business partners to research, develop, deploy and continuously improve machine learning solutions to drive growth and improve user experience for our customers. Responsibilities
As a member of the Customer Modeling Data Science team within Risk Management, develop machine learning algorithms and statistical models to optimize operations efficiency, drive effective marketing and personalized customer experience. Be constantly curious and continue to pursue in-depth explorations of our datasets. Collaborate with key stakeholders to understand business problems, ideate ML solutions and effectively communicate to stakeholders. Research, develop and apply ML/AI solutions to solve business problems, including prediction, optimization, segmentation and so on. Partner with Operations, Collections and Marketing teams to develop and deploy ML solutions into business processes. Continuous monitoring and evaluating model performance and communicating to relevant stakeholders. Conduct model-related analyses to provide comprehensive insights about ML solutions. Required Skills
MS/PhD or equivalent experience in quantitative fields such as Mathematics, Statistics, Computer Science or other STEM areas. 3+ years of industry modeling and machine learning experience with techniques such as clustering, linear and logistic regression, random forest, gradient boosting (GBM), XGBoost, SVM, neural networks (e.g., ANN, RNN, CNN). Must have multiple robust examples of using these techniques to build ML-driven products to solve business problems (e.g., prediction, optimization, segmentation). 3+ years experience as an ML scientist with proven ability in developing ML models in Python (preferred), R, PySpark or Java. Expert-level knowledge of SQL with strong data exploration and manipulation skills. Experience using AWS SageMaker or other cloud platforms (e.g., GCP) for model development, training and operationalization. Familiarity with Model Risk Management (MRM) frameworks and model governance best practices. Ability to communicate ideas and code clearly to business stakeholders. Ability to collaborate across multiple levels and teams (engineering, operations, marketing, etc.). Effective verbal/written communication and technical presentation skills. Self-starter with a passion for growth and continuous learning, and willingness to share findings across the team. Preferred Experience
Experience in Financial Services or FinTech. Experience in credit, fraud, automation and personalization/recommendation systems. Premium Medical, Dental, and Vision Insurance plans. Company-provided Basic Life and Short-Term Disability plans. Voluntary Life Insurance and Long-Term Disability plans. 401(k) savings plan with matching contributions. Healthcare and Dependent Care Flexible Spending Accounts (FSA). Generous and flexible 20 or 25 PTO days plus 8 holidays annually. A collaborative environment with opportunities for learning and growth. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Note: This description focuses on the Senior Data Scientist role and does not include extraneous postings or unrelated content.
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Title: Senior Data Scientist Location: Atlanta, GA or Austin, TX — Hybrid (3 days onsite, 2 days remote) Team Overview Atlanticus is looking for an experienced and passionate senior data scientist in our Risk Management team. This role will partner with collections, operations, marketing and other business partners to research, develop, deploy and continuously improve machine learning solutions to drive growth and improve user experience for our customers. Responsibilities
As a member of the Customer Modeling Data Science team within Risk Management, develop machine learning algorithms and statistical models to optimize operations efficiency, drive effective marketing and personalized customer experience. Be constantly curious and continue to pursue in-depth explorations of our datasets. Collaborate with key stakeholders to understand business problems, ideate ML solutions and effectively communicate to stakeholders. Research, develop and apply ML/AI solutions to solve business problems, including prediction, optimization, segmentation and so on. Partner with Operations, Collections and Marketing teams to develop and deploy ML solutions into business processes. Continuous monitoring and evaluating model performance and communicating to relevant stakeholders. Conduct model-related analyses to provide comprehensive insights about ML solutions. Required Skills
MS/PhD or equivalent experience in quantitative fields such as Mathematics, Statistics, Computer Science or other STEM areas. 3+ years of industry modeling and machine learning experience with techniques such as clustering, linear and logistic regression, random forest, gradient boosting (GBM), XGBoost, SVM, neural networks (e.g., ANN, RNN, CNN). Must have multiple robust examples of using these techniques to build ML-driven products to solve business problems (e.g., prediction, optimization, segmentation). 3+ years experience as an ML scientist with proven ability in developing ML models in Python (preferred), R, PySpark or Java. Expert-level knowledge of SQL with strong data exploration and manipulation skills. Experience using AWS SageMaker or other cloud platforms (e.g., GCP) for model development, training and operationalization. Familiarity with Model Risk Management (MRM) frameworks and model governance best practices. Ability to communicate ideas and code clearly to business stakeholders. Ability to collaborate across multiple levels and teams (engineering, operations, marketing, etc.). Effective verbal/written communication and technical presentation skills. Self-starter with a passion for growth and continuous learning, and willingness to share findings across the team. Preferred Experience
Experience in Financial Services or FinTech. Experience in credit, fraud, automation and personalization/recommendation systems. Premium Medical, Dental, and Vision Insurance plans. Company-provided Basic Life and Short-Term Disability plans. Voluntary Life Insurance and Long-Term Disability plans. 401(k) savings plan with matching contributions. Healthcare and Dependent Care Flexible Spending Accounts (FSA). Generous and flexible 20 or 25 PTO days plus 8 holidays annually. A collaborative environment with opportunities for learning and growth. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Note: This description focuses on the Senior Data Scientist role and does not include extraneous postings or unrelated content.
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