Truist is looking to leverage sophisticated analytics to improve business outcomes and minimize risk.
Requirements
- In-depth knowledge in practices, theories and methodologies associated with the professional discipline such as statistics, programming (such as Python, R, SAS, etc.), machine learning, model development, business information visualization, etc.
- Ability to maintain a high level of competency in statistical and analytical principles, tools, and techniques
- Working knowledge of Hadoop, Pig, Hive, and/or NoSQL, Spark
- Experience working with data science workspace within Adobe Enterprise Platform
- Experience working with Graph Databases, graph query language, and related algorithms
Responsibilities
- Perform sophisticated data analytics (encompassing data mining, inferential statistical analysis, and predictive analytics, for example) on structured and unstructured data.
- Identify actionable insights from various (or multiple) sources of data that measurably improve business outcomes or reduce business risk.
- Support new, ongoing, and strategic projects and take accountability and ownership of end-to-end data science solution design, technical delivery, and measurable business outcome.
- Extract and evaluate information gathered from multiple sources, resolve data conflicts and customize communication of key data findings, while providing recommendations to diverse audiences.
- Provide analytical consulting and thought leadership to various business areas and fosters strategic and positive relationship with business partners.
- Co-design the optimal solutions to solve the complex business problems with advanced data science capabilities to create business value.
- Actively research and advocate adoption of emerging methods and technologies in the data science field, with the eye of continually advancing Truist’s capabilities.
Other
- Perform sophisticated analytics (statistical and predictive analytics, machine learning modeling, etc.) to provide actionable insights that improve business outcomes and minimize risk.
- Provide consultation to business leaders and other stakeholders on how to leverage analytics insights and build strategies around analytics.
- Lead small projects with manageable risks and resource requirements; play significant roles in larger, more complex initiatives.
- Act as a resource for teammates with less experience.
- Demonstrate domain expertise (SME) in one or more areas relevant to banking, financial services, fin-tech, quantitative risk management, and/or financial regulation; this will be demonstrated by several years of career progression in roles of increasing responsibility
- Experience in managing multiple projects with tight deadlines in a collaborative environment
- English (Required)
