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The Enterprise Data & Analytics (ED&A) organization is seeking a Lead Data Scientist with strong analytical and algorithmic skills to optimize interest rates, portfolio outcomes, and acquisition strategies.
Key Responsibilities:
Design and build advanced decision support systems that facilitate robust scenario planning for various business decisions, including constrained optimization solutions for deposit interest rates, portfolio outcomes, and acquisition strategies
Serve as the lead modeler for machine learning models and analytic products, from design phase to development, deployment, and integration into larger business processes
Develop relationships with other data scientists as well as partners in Finance, Pricing & Profitability, Product, Data, and Technology Services, to collaboratively deliver transformational optimization capabilities
Invest in developing deep knowledge of business decision frameworks, operational processes, and data in order to successfully design & develop practicable solutions
Desired Profile:
Master’s degree in operations research, computer science, mathematics, statistics, economics, or related quantitative field and 8+ years of experience delivering quantitative decision tools for business applications (or PhD and 5+ years of experience)
Proven experience turning ambiguous business problems and raw data into rigorous analytic solutions by applying critical thinking and advanced technical & statistical programming techniques
Proficient in Python with 5+ years of applied experience
Proficient with one or more optimization modeling package and solver (e.g. CPLEX, SCIP, Pyomo, SciPy)
A deep understanding of the theory and application of a variety of statistical and machine learning methods and algorithms, including optimization under uncertainty, forecasting, time series analysis, and Bayesian methods
Excellent communication skills with both technical and non-technical audiences
Strong leadership and team management skills, including the ability to effectively lead both direct reports and complex, multi-team projects
Experience with cloud computing platforms (preferably AWS) and ML-related services such as Amazon Sagemaker.
A strong sense of intellectual curiosity and ability to thrive and deliver value in an entrepreneurial working environment
Commitment to intellectual rigor and observance of compliance and data privacy controls
A disciplined approach to making decisions and setting expectations
Experience working with large datasets (greater than 1 million records) and applying techniques to efficiently manage big data
Experience working with financial datasets (preferred).
Compensation Range: Upto $180k
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