Data Scientist: III (Senior)

Description

Our Enterprise Data and Analytics team is growing. We're looking for a Lead Data Scientist to assist with building and developing our Data Science team and lead us into the next generation of banking. We are reimagining how data is used across the bank to better serve our customers support our communities and make our colleagues lives better. Our goal is to be the best performing Regional Bank in America and we need data and analytics to meet that goal.

As we advance our data science and analytics capabilities we want a Lead Data Scientist to develop experts in modeling complex business problems and discovering business insights using statistical algorithmic mining and visualization techniques. We are looking for a leader who has a passion for developing others driving change and continuously improving and evolving the application of technologies to meet todays and tomorrow's challenges.

Key Responsibilities:

Prioritizes analytical projects based on business value and technological readiness

Performs large-scale experimentation and build data-driven models to answer business questions

Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence

Evangelizes best practices to analytics and products teams

Acts as the go-to resource for machine learning across a range of business needs

Owns the entire model development process, from identifying the business requirements, data sourcing, model fitting, presenting results, and production scoring

Provides leadership, coaching, and mentoring to team members and develops the team to work with all areas of the organization

Works with stakeholders to ensure that business needs are clearly understood and that services meet those needs

Anticipates and analyzes trends in technology while assessing the emerging technologies impact(s)

Requirements

Qualifications:

Minimum of 5 years of experience in statistics & ML, preferably within finance.

Up-to-date knowledge of machine learning and data analytics tools and techniques

Strong knowledge in predictive modeling methodology

Experienced at leveraging both structured and unstructured data sources

Willingness and ability to learn new technologies on the job

Demonstrated ability to communicate complex results to technical and non-technical audiences

Strategic, intellectually curious thinker with focus on outcomes

Professional image with the ability to form relationships across functions

Ability to train more junior analysts regarding day-to-day activities, as necessary

Proven ability to lead cross-functional teams

Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker)

Strong experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret)

Demonstrated Expertise with at least one Data Science environment (R/RStudio, Python, SAS) and at least one database architecture (SQL, NoSQL)

Financial Services background preferred.

Expert understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling.

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