Senior Director, Data Science, Analysis, & Visualization

Position Overview

Senior Director of Data Science, Analysis, & Visualization

development and scaling of Alkami’s advanced analytics capabilities. This highly visible

executive role is responsible for shaping the strategy, roadmap, and execution of all machine

learning, predictive analytics, and business intelligence initiatives across Alkami’s digital banking

and the marketing ecosystem.

This individual will oversee three core areas:

Data Science

acquisition, and personalization.

Data Analysis

Visualization & Reporting

tools for both internal teams and client-facing products.

As a thought leader, the Senior Director will work closely with Product, Engineering, Marketing,

and Client Success teams to integrate intelligent insights into every layer of the Alkami platform

— driving smarter acquisition, deeper engagement, and measurable growth for our financial

institution clients.

seasoned leader

environments, leading high-performing analytics teams, and translating complex data into

business value.

Key Responsibilities & Duties

Strategy & Leadership

• Define and drive Alkami’s strategy for data science, analytics, and reporting — aligning with corporate priorities around personalization, engagement, and monetization.
• Act as the senior-most leader for data science and analytics, representing these domains in executive forums and cross-functional planning.
• Build and manage a high-performance organization across data scientists, analysts, and visualization specialists (~10-15 team members).
• Collaborate across teams to embed analytics deeply into the product lifecycle — from data instrumentation to AI-powered insights and real-time reporting.
• Ensure our data tools and models are accessible, scalable, and aligned with both internal product needs and external client success.

Data Science Execution

• Lead the development of machine learning models for customer scoring, churn prediction, cross-sell/upsell, segmentation, and prospect targeting.
• Operationalize AI/ML outputs into platform features — powering campaign orchestration, customer engagement, and decision support tools.
• Champion model reliability, monitoring, and explainability, ensuring models are ethical, auditable, and regulatory-compliant.
• Drive innovation in predictive and prescriptive analytics by continuously evaluating emerging ML technologies and methods.

Data Analysis & Visualization

• Lead the development of dashboards and visualization tools that provide actionable insights to marketing, product, and executive teams.
• Oversee platform migration from legacy tools (e.g., MicroStrategy) to modern, AI-capable BI environments.
• Develop self-service analytics capabilities that empower both internal teams and financial institution clients with fast, flexible access to insights.
• Drive adoption and usage of data tools across the organization by designing user-friendly, role-based experiences.

Qualifications

Required

• 15+ years

  of experience in data science, analytics, or related fields, with

  7+ years

  in a senior leadership role managing multidisciplinary teams.
• Demonstrated success leading AI/ML initiatives

  from strategy through deployment

  in production environments — preferably in SaaS or fintech.
• Deep technical expertise in machine learning, statistical modeling, and data visualization.
• Proven ability to manage the full analytics lifecycle: data acquisition, cleansing, modeling, visualization, and business application.
• Strong command of tools like Python, SQL, R, and modern data stack components (e.g., Snowflake, dbt, Tableau, Power BI, Looker).
• Experience with cloud-based ML platforms and MLOps (e.g., AWS SageMaker, Vertex AI, MLflow, etc.).
• Track record of mentoring senior data leaders and building scalable data teams.
• Ability to communicate complex analytical concepts to executive audiences in clear, business-focused language.
• Strong business acumen with a passion for solving real-world problems through data.
• Bachelor’s degree in Data Science, Computer Science, Mathematics, or related field; Master’s or Ph.D. preferred.

Preferred

• Experience in financial services, banking technology, or martech.
• Familiarity with customer data platforms (CDPs), segmentation frameworks, and digital engagement KPIs.
• Understanding of data privacy and compliance frameworks (e.g., GDPR, CCPA, FFIEC).