Reporting Data Scientist III

Key Skills

Machine learning techniques, Predictive Modeling, Python Programming, R Programming, SAS, Statistical modeling

Job Description

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 data and reporting. Lead small projects with manageable risks and resource requirements; play significant roles in larger, more complex initiatives help build and deliver solutions that collect, transform, analyze, and report data—strategic and tactical as well as operational. Act as a resource for teammates with less experience.

ESSENTIAL DUTIES AND RESPONSIBILITIES

Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time.

• Enhance the team’s abilities to report on performance, focus on impact, and provide transparency around Fraud Operations work streams with creative and innovative storytelling.
• Provide insights and analytics to identify notable trends to optimize operations performance and minimize fraud risk.
• Identify and isolate emerging trends and actionable insights that will assist in making internal risk-based strategic decisions.
• 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 reporting and data 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. Emphasize reusability and scalability in all design, development, deployment and mentoring activities through implementing consistent coding standards and best practices, focusing on clarity of communication across stakeholder groups and maintaining rigorous documentation.
• Exercise sound judgment and foster 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; help with the overall risk management for the team.
• Actively research and advocate adoption of emerging methods and technologies in the data science field, with the eye of continually advancing Truist’s capabilities.

QUALIFICATIONS

Required Qualifications:

The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Bachelor’s degree in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering, or equivalent education and related training
• Minimum of six years of related 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
• 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 in managing multiple projects with tight deadlines in a collaborative environment

Preferred Qualifications:

• Master’s degree or PhD in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering
• Strong experience with SQL, including writing complex queries and optimizing database performance.
• Knowledge of Tableau, including experience creating and deploying interactive dashboards.
• Expertise working with large datasets and knowledge of data visualization best practices.
• 5 Ability to design and implement reports that meet business requirements and are easy to use.
• Familiarity with data warehousing concepts and methodologies
• 3+ years’ experience working with qualitative and quantitative analytics methodologies.
• 5+ years of recent development experience in utilizing SQL, Python, R, Java, .NET with the ability to build data integration processes
• Previous experience in the banking or fin-tech industry