Technology & Operations Senior Business Analyst (Analystics)

Truist•Atlanta, GA

1d•Onsite

About The Position

The Technology & Operations Senior Business Analyst (Analytics) partners with Technology & Operations leaders, business stakeholders, and Analytics teammates to solve complex business problems through advanced analytics, strategic consultation, and scalable reporting solutions. This role requires a deeper level of practical experience translating ambiguous business needs into structured requirements, governed metrics, and enterprise-ready data solutions. Serving as a senior individual contributor, the role operates with greater independence and judgment, influencing priorities, identifying risks and dependencies, and ensuring analytics products are aligned to business strategy, operational performance goals, and control requirements. The Senior Business Analyst leads complex, high-visibility work such as Power BI dashboard modernization, metric strategy and performance measurement design, data foundation enhancement, and workflow enablement using SharePoint and Power Platform tools. This position calls for stronger analytical and technical skills, sound business acumen, and demonstrated experience delivering production solutions that improve decision-making, increase automation, strengthen controls, and reduce manual effort across lines of business. Success in this role includes guiding less experienced analysts, driving clarity across cross-functional teams, and applying hands-on experience to deliver sustainable solutions.

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

Nice To Haves

Bachelor’s degree such as Business, Analytics, Information Systems, Operations, or related
5-10+ years of relevant work experience in business analysis/reporting, operations enablement or workflow automation
Previous experience in the banking or fin-tech industry helpful

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. 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.