Principal Data Scientist - Advanced Analytics

Vericast; San Antonio (TX); On-site; USD 170,000 - 200,000; Full time

Job summary

Vericast is seeking a Principal Data Scientist to lead advanced analytics, experimentation, and machine learning initiatives. Based in the United States, you will shape analytics strategy with senior stakeholders and build scalable AI solutions that unlock measurable business impact.

You will collaborate across Product, Marketing, IT, Risk, and Compliance to translate complex challenges into testable hypotheses and data-driven recommendations that fuel growth.

Qualifications

• Master's degree in statistics, data science, CS, economics or related quantitative field.
• PhD strongly preferred in statistics, data science or related field.
• Relevant data science or cloud certifications are a plus.

Responsibilities

• Design end-to-end experimentation strategies and metrics.
• Build and deploy ML and GenAI solutions at scale.
• Partner with executives and cross-functional teams to drive business impact.

Skills

Experimentation

A/B testing

Causal inference

ML modeling

GenAI

Data pipelines

Education

Master's degree in Statistics/Data Science/CS

PhD in Statistics/Data Science

Certifications in data science/cloud

Tools

Python

SQL

Spark

AWS/GCP

Job description

Principal Data Scientist - Advanced Analytics

• Full-time
• Shift: 1st
• Compensation: USD 170,000 - USD 200,000 - yearly

Vericast is the financial institution (FI) performance partner. We help banks and credit unions drive growth, improve efficiency, increase engagement and navigate change through the power of data, technology and people. Our advanced analytics, data-driven insights and integrated solution set enable better execution with agility, precision and scale. That's why thousands of financial institutions look to Vericast and our 150 years of financial services expertise to help them achieve more.

Vericast is investing in the next generation of Advanced Analytics, Experimentation, and Measurement, and we're looking for a Principal Data Scientist to help lead the way. This is a highly visible opportunity for a data science leader who thrives at the intersection of experimentation, causal inference, machine learning, and Generative AI.

In this role, you'll shape our analytics discipline from the ground up, partnering with executive leaders and cross-functional teams to solve complex business challenges with data. You'll design rigorous experimentation frameworks, build and deploy scalable AI and machine learning solutions, and transform complex insights into clear recommendations that drive growth and measurable business impact.

This is a senior individual contributor role that offers the opportunity to influence strategy, establish best practices, mentor other data scientists, and leave a lasting mark on how Vericast leverages data to make decisions.

What You'll Do

Lead Experimentation & Measurement Strategy (40%)

• Own the end-to-end design, execution, and analysis of marketing and product experiments, including A/B, multivariate, geo, and holdout testing.
• Define and manage the experimentation roadmap, including hypothesis development, prioritization, power analysis, and success metrics.
• Develop and refine methodologies for lift measurement, incrementality testing, and causal inference.
• Establish standards, governance, and best practices that ensure statistical rigor and actionable insights across the organization.
• Partner with stakeholders to build a culture of experimentation and data-driven decision making.

Drive Advanced Analytics, Machine Learning & GenAI Innovation (40%)

• Design, build, validate, and deploy machine learning and Generative AI solutions using large-scale structured and unstructured data.
• Develop predictive, prescriptive, attribution, market mix, and uplift models that drive measurable business outcomes.
• Lead hands-on model development, coding, testing, and production deployment while establishing technical standards for the broader team.
• Create and maintain robust data pipelines to ensure data quality, integrity, and scalability.
• Continuously evaluate emerging technologies and analytical approaches to improve performance and business value.

Influence the Business Through Strategic Partnership (20%)

• Collaborate with Product, Marketing, Sales, IT, Risk, and Compliance teams to identify, prioritize, and solve high-value business opportunities.
• Translate complex business challenges into testable hypotheses and analytical solutions.
• Present findings and recommendations to both technical and executive audiences in a clear and compelling way.
• Serve as a trusted advisor and subject matter expert on experimentation, analytics, AI, and machine learning.
• Mentor and elevate fellow data scientists through coaching, technical guidance, and best-practice sharing.

Education

• Master's degree in Statistics, Data Science, Computer Science, Economics, Mathematics, Engineering, or a related quantitative field required.
• PhD in Statistics, Data Science, or a related quantitative discipline strongly preferred.
• Relevant data science, machine learning, or cloud certifications are a plus.

Experience

• 8+ years of progressive experience in data science, analytics, or machine learning roles with significant hands-on experience working with large-scale data environments.
• Experience within financial services or another highly regulated, data-intensive industry preferred.
• Proven success leading or serving as a senior technical contributor on experimentation, measurement, and advanced analytics initiatives.
• Demonstrated ability to translate complex business challenges into scalable analytical solutions that drive measurable business outcomes.
• Experience influencing senior stakeholders and partnering with cross-functional teams to deliver data-driven insights and recommendations.

What Will Make You Successful

Experimentation, Measurement & Statistical Expertise

• Deep expertise in marketing experimentation, including A/B testing, multivariate testing, experimental design, metric development, and lift/incrementality measurement.
• Strong background in causal inference methodologies, hypothesis testing, statistical modeling, and power analysis.
• Proven ability to design, execute, validate, and scale experimentation programs that enable confident business decision-making.
• Experience establishing governance, best practices, and standards for experimentation across an organization.

Machine Learning, GenAI & Technical Skills

• Hands-on experience developing and deploying Market Mix Models (MMM), Attribution Models, and Uplift Models.
• Strong experience working with Machine Learning, Large Language Models (LLMs), Generative AI solutions, and emerging agent-based frameworks such