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Company Overview
A leading financial services organization specializes in data-driven decision-making and personalized customer experiences. Leveraging advanced analytics, machine learning, and cutting-edge technologies, the organization delivers innovative digital products that empower customers to make smarter financial decisions. Their Consumer Identity Machine Learning team focuses on real-time, intelligent, and personalized experiences across web, mobile, email, and chat platforms, partnering closely with product and engineering teams to drive actionable insights and business outcomes.
Summary
The Manager, Data Science – Consumer Identity Machine Learning will work across all phases of the data science lifecycle to develop models that anticipate customer needs, enhance digital experiences, and maintain data integrity. This role combines strategic thinking, technical expertise, and leadership in machine learning and big data analytics to impact millions of customers.
Responsibilities
Build and operationalize machine learning models from design through training, evaluation, validation, and production deployment for scalable systems serving 50+ million customers
Analyze billions of customer events to identify behavioral patterns and develop models to predict key outcomes
Partner with business and product teams to design and execute experiments that improve customer experiences across marketing, servicing, and fraud prevention
Write software in open-source languages (e.g., Python, Scala, R) to collect, explore, visualize, and analyze large-scale numerical and textual datasets using tools such as Spark
Ensure critical customer data accuracy, fight fraud, and enable seamless digital experiences
Stay current with emerging data science methods, technologies, and applications, and apply innovative approaches to complex problems
Provide technical guidance and mentorship to junior team members
Qualifications
Basic Qualifications
Bachelor’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) plus 6 years of experience in data analytics OR
Master’s Degree in a quantitative field OR MBA with quantitative concentration plus 4 years of experience in data analytics OR
PhD in a quantitative field plus 1 year of experience in data analytics
At least 1 year of experience using open-source programming languages for large-scale data analysis
At least 1 year of experience with machine learning
At least 1 year of experience using relational databases
Preferred Qualifications
PhD in STEM field plus 3 years of experience in data analytics
At least 1 year of experience working with AWS
At least 4 years of experience in Python, Scala, or R for large-scale data analysis
At least 4 years of experience with machine learning
At least 4 years of experience with SQL
Disclaimer
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1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality. 2. No Client Relationship: This company is not a client of SpringCube unless stated. 3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job. 4. No Liability: SpringCube is not liable for inaccuracies.
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