Data Scientist III- Human Capital Data and Analytics Enablement

Truist•Charlotte, NC

1d•Onsite

About The Position

The Data Scientist III designs and delivers analytics-driven digital products that enable executive and business-unit leadership to make informed, data-driven decisions. This role goes beyond traditional analysis by owning the end-to-end creation of scalable dashboards, tools, and analytical solutions that surface key metrics, trends, and predictive insights for senior leaders. As a self-starter, this individual will help shape the role and analytics roadmap, working closely with mid-level and executive leadership to gather requirements, translate business questions into analytical frameworks, and design intuitive, high-impact dashboards and reporting experiences. These digital products will allow leaders to securely sign in and monitor the performance, risks, and opportunities within their business units in near real time. The Data Scientist III performs advanced analytics using human capital data sourced from the cloud. The role partners closely with HR and data engineering teams as the Snowflake environment continues to mature, ensuring data quality, usability, and analytical readiness. In addition to hands-on development, this role acts as a trusted analytics advisor, consulting with stakeholders on how to interpret insights, embed analytics into decision-making, and build strategies around data. The Data Scientist III leads smaller, well-scoped projects independently, plays key roles on larger, more complex initiatives, and serves as a resource and mentor to less-experienced analysts and data scientists. For this opportunity, Truist will not sponsor an applicant for work visa status or employment authorization, nor will we offer any immigration-related support for this position (including, but not limited to H-1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN-1 or TN-2, E-3, O-1, or future sponsorship for U.S. lawful permanent residence status.)

Requirements

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 Snowflake, Hadoop, Pig, Hive, and/or NoSQL, Spark
Experience in managing multiple projects with tight deadlines in a collaborative environment

Nice To Haves

Master’s degree or PhD in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering
Ten years of relevant work experience if candidate lacks graduate degree
Previous experience in the banking or fin-tech industry
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 (including building the visualization using Tableau, Qlik ,Sigma or another enterprise sanctioned tool), 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.