Data Scientist - Credit Risk

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What you'll be doing...

As a Consultant (Analytics) you will own and perform specific analytics tasks as well as lead and drive end to end solutions for AI/ML use cases with guidance from lead / manager.

Responsibilities include:

• Driving data-derived insights across the business domain by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives.
• Directing the gathering of data, assessing data validity and synthesizing data into large analytics datasets to support project goals.
• Analyzing structured and unstructured data using data mining/statistical/machine learning/deep learning tools, Data visualization, Digital/Web analytics tools and techniques and storytelling.
• Building and training statistical models and machine learning algorithms.
• Performing tasks related to Operationalization - e.g., wrapper script, REST service, Trigger, Monitoring etc.
• Preparing all the supporting documents and reports.
• Mentoring/Guiding one to two members in the team on technical aspects as needed.

What we're looking for...

You have strong analytical skills, and are eager to work in a collaborative environment with global teams to drive ML application in business problems, develop end to end analytical solutions and communicate insights and findings to leadership. You work independently and are always willing to learn new technologies. You thrive in a dynamic environment and are able to interact with various partners and multi-functional teams to implement data science driven business solutions.

You'll need to have:

• Bachelor's degree or four or more years of work experience.
• Four or more years of relevant work experience.
• Four or more years of experience in advanced analytics/ predictive modelling in a consulting role.
• Experience with all phases of end-to-end Analytics project, such as (but not limited to): Ingestion, Munging, Model Building, Validation, Operationalization, Monitoring.
• Experience building models using statistical techniques such as Supervised and Unsupervised Machine Learning models, Deep learning, Text classification etc.
• Knowledge of Python, Sql, PySpark, Scala and/or other languages and tools.

Even better if you have one or more of the following:

• Experience applying machine learning in a credit or banking use case.
• Extensive experience in Loan Loss Forecasting, including developing PD, LGD, risk rating, and cash flow models.
• Experience automating and productionalizing credit model processes and documentation using gitlab & Sphinx.
• Ability to engage with larger credit organizations, including presentations, instructional meetings, and code reviews.
• A Master's degree in a quantitative discipline such as Mathematics, Statistics, Financial Economics/Econometrics, Engineering, Computer Science, or Operations Research.
• Experience in visual science / dashboard design principles.
• Experience in applying statistical ideas and methods to data sets to answer business problems.
• Experience with programming languages, like Python, SQL, or R.
• Experience with Machine Learning algorithms and tools.

If Verizon and this role sound like a fit for you, we encourage you to apply even if you don't meet every "even better" qualification listed above.

We're proud to be an equal opportunity employer - and celebrate our employees' differences, including race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, and Veteran status. At Verizon, we know that diversity makes us stronger. We are committed to a collaborative, inclusive environment that encourages authenticity and fosters a sense of belonging. We strive for everyone to feel valued, connected, and empowered to reach their potential and contribute their best. Check out our diversity and inclusion page to learn more.