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Company Overview
A leading financial services organization has transformed the credit card industry through innovative, data-driven solutions. From its early use of statistical modeling to personalize offers, the company has grown into a Fortune 200 organization and a global leader in AI-enabled analytics and machine learning, helping millions of customers optimize their financial decisions.
Overview
The Manager, Data Science – AI for Data will lead teams in leveraging large-scale data and emerging AI/ML technologies to drive innovative solutions across the organization. The role requires hands-on technical expertise, strong leadership, and the ability to translate complex analytics into impactful business outcomes.
Team Description
The AI for Data team partners with Enterprise Data Product, Tech, and Design teams to develop AI-enabled features integrated across the data lifecycle. This team drives experimentation, innovation, and creation of next-generation AI/ML-powered experiences.
Role Description
Lead cross-functional teams of data scientists, software engineers, and product managers to deliver AI-driven products
Use technologies including Python, Conda, AWS, H2O, and Spark to extract insights from large numeric and textual datasets
Build machine learning models across all phases: design, training, evaluation, validation, and implementation
Translate complex technical concepts into actionable business goals for stakeholders
Navigate ambiguity, competing priorities, and tight deadlines while maintaining high-quality deliverables
Iterate rapidly with researchers and engineers to refine product experiences and enhance the platform
Ideal Candidate
Creative: Enjoys defining big, ambiguous problems and proposing innovative solutions
Technical: Experienced in open-source programming, cloud computing platforms, and data science tools
Statistically-minded: Skilled in model building, validation, backtesting, clustering, classification, sentiment analysis, time series, and deep learning
Data Guru: Comfortable working with large and diverse datasets, combining multiple data sources to generate insights
Basic Qualifications
Bachelor’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) with 6 years of data analytics experience
OR Master’s Degree in a quantitative field or MBA with a quantitative concentration plus 4 years of data analytics experience
OR PhD in a quantitative field plus 1 year of data analytics experience
Minimum 1 year experience leveraging open-source programming for large-scale data analysis
Minimum 1 year experience with machine learning
Minimum 1 year experience using relational databases
Preferred Qualifications
PhD in STEM field with 3 years of experience in data analytics
At least 1 year experience with AWS
Minimum 4 years experience in Python and SQL
Minimum 4 years experience with deep learning frameworks such as TensorFlow or PyTorch for large-scale neural network training and deployment
Minimum 4 years experience in Natural Language Processing, Information Retrieval, Search, Recommendations, and fine-tuning LLMs for specific applications
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