Data Scientist II

Truist•Charlotte, NC

6d•Hybrid

About The Position

The Data Scientist II position involves performing sophisticated analytics, including statistical and predictive modeling, machine learning, and natural language processing, to provide actionable insights that improve business outcomes and minimize risk. The role also includes consulting with business leaders and stakeholders on leveraging these insights and building analytics strategies. The position requires end-to-end ownership of data science solution design, technical delivery, and measurable business outcomes. It involves engaging in stakeholder meetings to define business objectives and solution requirements, writing, documenting, and deploying custom code in various environments (Python, SAS, R) for predictive analytics applications, and collaborating through internal code repositories to foster learning and skill-sharing. The role also requires researching and advocating for emerging data science methods and technologies to advance the company's capabilities, while exercising sound judgment and promoting risk management in design, development, and deployment practices, in partnership with cross-functional teams on data governance and usage.

Requirements

Bachelor’s degree in Data Science, Analytics, Computer Science, MIS or a quantitative field
4 years of experience in quantitative or data analytics positions
Experience performing/utilizing statistical methods, including a broad understanding of classical statistics, probability theory, econometrics, time-series, and primary statistical tests
Experience with data cleansing and preparation methodologies, including regex, filtering, indexing, interpolation, and outlier treatment.
Experience with Data Analysis techniques, EDA, Data Visualization to effectively communicate to stakeholders, clarify requirements and make effective suggestions.
Experience with Natural Language Processing techniques and other related Deep Learning knowledge.
Experience managing multiple projects with tight deadlines in a collaborative environment.
Utilizing experience with: SQL, SAS, Python, R, Pandas, NumPy, Tableau, Hadoop, and Unix Putty.

Responsibilities

Perform sophisticated analytics (statistical and predictive analytics, machine learning modeling, etc.) to provide actionable insights that improve business outcomes and minimize risk and also provide consultation to business leaders and other stakeholders on how to leverage analytics insights and build strategies around analytics.
Independently perform sophisticated data analytics (ranging from classical econometrics to machine learning, neural networks, and natural language processing) in a variety of environments using structured and unstructured data.
Produce compelling data visualizations to communicate insights and influence outcomes among a wide array of stakeholders.
Take accountability and ownership of end-to-end data science solution design, technical delivery, and measurable business outcome.
Engage in stakeholder meetings to identify business objectives and scope solution requirements.
Independently write, document, and deploy custom code in a variety of environments (Python, SAS, R, etc.) to create predictive analytics applications.
Use, maintain, share and collaborate through Truist internal code repositories to foster continual learning and cross-pollination of skillsets.
Actively research and advocate adoption of emerging methods and technologies in the data science field, with the eye of continually advancing Truist’s capabilities.
Exercise sound judgment and fosters risk management culture throughout design, development, and deployment practices; partner with cross-functional teams to coordinate rules on data usage, data governance and analytics capabilities.