Gathering your results ...
29 days
Not Specified
Not Specified
$42.60/hr - $77.42/hr (Estimated)
<p>Lead complex data science projects, ensuring they meet business objectives and deliver actionable insights. Develop advanced data models and algorithms to analyze large datasets and solve complex business problems. Collaborate with senior leadership to identify data-driven opportunities for business growth and efficiency. Implement best practices for data management, analysis, and visualization. Ensure data governance and compliance with relevant regulations and standards. Provide mentorship and technical guidance to the data science team. 8+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. Experience leading others New Data Sources Identify, evaluate, and onboard data sources for new credit product launches, including in new countries across the globe. Rapidly evaluate the potential of external data in predictive modeling and decisioning, including using AI/ML techniques. Build, lead, and develop a small high-performing team. Collaborate cross-functionally with Credit Risk, Fraud Risk, Machine Learning, Artificial Intelligence, Vendor Management, Data Platform, Data Operations, Legal, and Compliance teams. Lead strategic partnerships and contract negotiations with external data vendors. Track record of building and managing a high-performing team and fostering a culture of innovation, accountability, and focus on the customer. Strategic thinker with a deep understanding of how data can be leveraged to manage credit risk (understanding of fraud risk and marketing for lending products strong bonuses). Experience working with credit bureau and alternative data sources, with a track record of deploying these assets to drive business impact in lending or credit risk functions. Experience working in a highly matrixed environment and successfully collaborating with multiple partner teams to deliver meaningful impact. Working knowledge of how AI/ML techniques can enhance data value and ability to collaborate closely with machine learning and AI teams. Understanding of relevant regulatory environments (e.g., FCRA, ECOA, GLBA, GDPR), especially as they apply to data sourcing and usage. Trusted relationship builder with external data providers and internal stakeholders, including managing sensitive negotiations and long-term partnerships.</p>
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