Decision Science Lead

Truist•Atlanta, GA

21h•Onsite

About The Position

We are seeking a strategic and intellectually curious Decision Science leader to drive data-informed decisions and measurable business results. This role partners closely with key stakeholders to solve complex business problems, identify growth opportunities, and influence strategic priorities through advanced analytics, machine learning, and AI-driven insights. The successful candidate will lead analytical initiatives from data exploration through model development and insight generation, partnering across strategy, product, technology, and data teams to deliver solutions that improve decision-making and business performance. Success in this role requires strong business acumen, executive communication skills, and the ability to translate complex analyses into clear, actionable recommendations that influence leaders and drive quantifiable outcomes.

Requirements

The incumbent must demonstrate a combination of academic aptitude, quantitative skills, business acumen, working knowledge of transaction processing application software, application processing systems, and collection inventory systems, strategic and creative thinking, and excellent written and verbal communications skills
Bachelor’s degree or equivalent education and 7+ years of experience in Banking, Finance, Decision/Data Science, Analytics, Computer Science, Applied Mathematics or Engineering, or equivalent education and related training or experience
4+ years of decision science/analytics project management experience with a diverse project focus and demonstrated results
Must act as role model, able to perform in a cross-functional and collaborative team environment focused on supporting business partners with enhanced insights
Demonstrated ability to engage and manage a diverse set of internal business partners, product sets, and projects, connecting insights with execution and business impact
Innovative and strategic thinker with ability to connect to practical application, providing leadership on target initiatives, with a strong bias to action and focus on quantifiable business impact
Experience in managing multiple projects with tight deadlines in a collaborative environment, with ability to pivot and align resources to drive maximum impact
Ability to maintain a high level of competency in statistical and analytical principles, tools, and techniques. Champion application of emerging decision science techniques by supporting teammate training and development and building business partner awareness
Incumbent should have an understanding of various database environments (IBM DB2, Oracle), technical programming skills (SAS, SQL, Toad), exposure to applied data science tools (R, Python, SAS E-Miner), familiarity with data visualization and BI tools (Tableau, MicroStrategy), and demonstrated proficiency in Microsoft Office Suite (Excel, PowerPoint, Word)

Nice To Haves

Master’s or PhD in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering
10+ years of experience in Banking, Finance, Decision/Data Science, Analytics, Computer Science, Applied Mathematics or Engineering
2+ years of analytics management experience with a diverse project focus and demonstrated results

Responsibilities

Responsible for mentoring and acting as a force multiplier in support of Decision Scientists, with a focus on high impact, visible analyses and initiatives across multiple business models, covering banking channels, segments, and products.
Lead on target initiatives as assigned; work independently to drive decision science projects leveraging quantitative analysis techniques, including machine learning, in pursuit of business optimization and impact.
Foster communication and partnership across multiple levels of the organization including engagement with LOB leaders and senior managers. Responsible for stewarding relationships, delivering on promises, and building trust with partners while delivering on LOB and company goals.
Pursue business outcomes valued through increased revenue and/or efficiency leveraging data-driven insights powered by analytics in support of enhanced decision-making. Focus on continuous improvement in decision science delivery and outcomes in pursuit of business optimization.
Champion the use of tools to solve business challenges and deliver solutions that are timely, accurate, and repeatable.
Exercise sound judgment, risk management, and foster a client centric culture throughout design, development, and deployment practices.
Represent assigned business group in various forums, work streams, and executive reviews. Cultivate relationships with partner federated and hub analytics teams to drive efficient decision science delivery against shared objectives.