Analyzing and interpreting large datasets to uncover potential revenue generation opportunities and develop effective risk management strategies
Collaborating with key stakeholders to comprehend business problems and presenting recommendations based on the findings
Working with complex database tables and datasets to extract, transform, and prepare data for model features and analytical workflows
Completing end-to-end model development work, ranging from supervised, unsupervised, and graph-based machine learning solutions
Building models such as linear/logistic regression, tree-based models (Random Forest, Gradient Boosting), NLP, and Time-series models
Enabling business analytics, including data analysis, trend identification, and pattern recognition, to drive decision-making insights
Ensuring proper documentation of datasets, analytical methods, and model assumptions to maintain reproducibility and transparency
Performing advanced analytics to identify and prioritize densely connected fraud networks, leveraging cross-portfolio and graph data
Managing relationships with multiple technology teams, development team, and line of business partners, ensuring alignment of roadmaps, project execution, and risk management
Delivering engaging and effective presentations in both in-person and virtual settings to communicate technical concepts and analytical results to a diverse set of internal stakeholders

3+ years experience in data and analytics
Must be proficient with SQL and one of SAS, Python, or Java
Exposure to model development leveraging supervised and unsupervised machine learning (regression, tree-based algorithms, etc.)
Problem-solving skills including selection of data and deployment of solutions
Experience providing thought leadership, developing deliverables, and working with limited direction on complex problems to achieve project goals
Effective communication and influencing skills
Thrives in fast-paced and highly dynamic environment
Intellectual curiosity and strong urge to figure out the “whys” of a problem and produce creative solutions
Experience handling and manipulating data across its lifecycle in a variety of formats, sizes, and storage technologies to solve a problem (e.g., structured, semi-structured, unstructured; graph; Hadoop; Kafka)
Expertise in data analytics and/or technical development lifecycles.

This role is currently benefits eligible.
We provide industry-leading benefits, access to paid time off, resources and support to our employees so they can make a genuine impact and contribute to the sustainable growth of our business and the communities we serve.

Data Scientist I – Client Protection, Modeling

Key skills