Overview of Position

Own analytics that directly influence Finance strategy. Partner with leaders to translate business needs into insights, and build toward AI- and advanced analytics–driven solutions that accelerate impact. You’ll operate independently, collaborate as a technical peer with engineers and fellow BI analysts, and see your work drive real decisions. This role is ideal for someone with 1–3 years of experience who wants end-to-end ownership of analytical problems and brings the technical foundation and curiosity to grow in AI-powered analytics.

Responsibilities

We're building the next generation of Finance analytics, moving from static reporting to dynamic, AI-assisted insights that the CFO organization relies on daily. This role sits at that center: you'll maintain our existing financial data foundation while designing and deploying new analytics products that drive decisions on FP&A, liquidity management, and financial performance, increasingly with AI-powered workflows.

• Write clean, well-documented SQL and Python that others can maintain and build on; learn to apply agentic AI to financial analytics workflows, automating insight generation, explaining anomalies in data, and accelerating report narratives

• Build dashboards and data applications Finance teams actually use, and improve them based on real feedback

• Validate data accuracy against business expectations and collaborate with data engineering and our data governance program to identify and resolve data quality issues

• Translate analytical findings into clear narratives for Finance leadership, including the CFO and other senior stakeholders

• Collaborate with senior analytics developers on AI integration: help design and test LLM-powered analytics workflows, learning prompt engineering, tool use, and multi-step reasoning for financial analysis

• Proactively spot gaps in existing analytics and propose solutions, including where AI tooling could unlock new capabilities

• Participate in code reviews and communities of practice to share learnings and contribute to the growing AI analytics practice within the organization

Required Qualifications

• 1–3 years of hands-on experience in analytics or data science

• Proficiency in SQL and Python; comfortable writing production-quality, version-controlled code

• Familiarity with dimensional modeling and cloud data warehouses; Snowflake experience is a plus

• Hands-on experience building dashboards in at least one modern BI tool (Power BI, Sigma, Looker, or similar)

• Able to communicate technical work clearly to non-technical audiences

• Bachelor's degree in a quantitative field (Computer Science, Data Science, Statistics, Engineering, or related) required

Preferred Qualifications

• Foundational knowledge of AI and LLMs: basic understanding of how language models work, prompt engineering concepts, and API integration

• Background in financial reporting, FP&A, or related Finance operations

• Experience with Streamlit or Posit for analytical applications

• Comfortable with code reviews, version control, and iterative delivery

• Demonstrated eagerness to learn AI development with a growth mindset

The duties listed above are the essential functions, or fundamental duties within the job classification.  The essential functions of individual positions within the classification may differ. Texas Capital Bank may assign reasonably related additional duties to individual employees consistent with standard departmental policy.Texas Capital is an Equal Opportunity Employer.