Principal Data Scientist - Advanced Analytics

Description

The company is expanding its advanced analytics, experimentation and measurement work and is hiring a Principal Data Scientist to lead it. The role suits a data science leader who works across experimentation, causal inference, machine learning and generative AI.

You will build the analytics function largely from the ground up, working with senior executives and cross-functional teams to answer hard business questions with data. The work includes designing sound experiment frameworks and building scalable AI and ML systems, then turning results into plain recommendations that support growth.

This is a senior individual contributor position. You will shape strategy, set best practices, mentor data scientists and influence how the company uses data to make decisions.

The company is a financial institution performance partner. It helps banks and credit unions grow, improve efficiency, deepen engagement and manage change using data, technology and people, and it serves thousands of financial institutions with 150 years of financial services experience.

Responsibilities

• Experimentation and measurement strategy (40%)
• Run end-to-end design, execution and analysis of marketing and product tests, including A/B, multivariate, geo and holdout tests.
• Own the experiment pipeline: hypotheses, prioritization, power analysis and success metrics.
• Build and improve methods for lift, incrementality and causal inference.
• Set standards and governance so tests are statistically sound and results are usable across the organization.
• Work with stakeholders to make experimentation and data-based decisions routine.
• Advanced analytics, machine learning and GenAI innovation (40%)
• Design, build, validate and ship ML and generative AI solutions on large structured and unstructured datasets.
• Build predictive, prescriptive, attribution, market mix and uplift models that move business metrics.
• Lead hands-on modeling, coding, testing and production deployment while setting technical standards for the team.
• Build and maintain data pipelines that keep data accurate, consistent and scalable.
• Track new tools and methods and test whether they improve performance or add value.
• Business partnership (20%)
• Work with Product, Marketing, Sales, IT, Risk and Compliance to identify, rank and solve high-value opportunities.
• Turn complex business problems into testable hypotheses and analysis plans.
• Present findings to technical and executive audiences in a clear, persuasive way.
• Act as trusted advisor and subject matter expert on experimentation, analytics, AI and ML.
• Coach other data scientists and raise their level through technical guidance and shared best practice.

Requirements

• 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.
• Data science, machine learning or cloud certifications are a plus.
• Experience
• At least 8 years of progressive experience in data science, analytics or machine learning, including substantial hands-on work with large-scale data.
• Experience in financial services or another highly regulated, data-intensive industry, preferred.
• A record of leading, or serving as senior technical contributor on, experimentation, measurement and advanced analytics initiatives.
• Ability to turn complex business challenges into scalable analysis that produces measurable results.
• Experience influencing senior stakeholders and working with cross-functional teams to deliver insights and recommendations.
• Experimentation and statistics
• Deep expertise in marketing experimentation, including A/B and multivariate testing, experimental design, metric development, and lift and incrementality measurement.
• Strong grounding in causal inference, hypothesis testing, statistical modeling and power analysis.
• Proven ability to design, run, validate and scale experimentation programs that support confident decisions.
• Experience setting governance, best practices and standards for experimentation across an organization.
• Machine learning, GenAI and technical skills
• Hands-on experience developing and deploying market mix, attribution and uplift models.
• Strong experience with machine learning, large language models, generative AI and agent-based frameworks such as LangChain, LangSmith or similar.
• Working knowledge of clustering, classification, regression, neural networks, anomaly detection, recommendation engines and predictive modeling.
• Advanced programming in Python, Spark/PySpark and SQL.
• Experience with cloud data platforms such as Databricks, Snowflake or similar data lake environments.
• Experience building and deploying solutions in AWS and Azure.
• Familiarity with Kubernetes, Docker and Git.
• Experience with data visualization and business intelligence tools, Tableau preferred.
• Familiarity with data science platforms such as Dataiku is a plus.
• Leadership and communication
• Ability to work in ambiguous settings while bringing clarity, prioritization and business results.
• Excellent communication and storytelling, turning complex analysis into practical executive-level recommendations.
• Experience mentoring and giving technical leadership to data scientists and analytics professionals.
• Strong analytical reasoning, problem solving and attention to detail.
• Ability to juggle several priorities and deliver results in a quick-moving setting.
• Proven record of collaborating across Product, Marketing, Sales, IT, Risk, Compliance and other business functions.
• Commitment to building a data-driven culture grounded in rigorous experimentation, innovation and continuous improvement.

Conditions

Applications close on November 13, 2026, or sooner if a sufficient candidate pool is identified.

The company values collaboration, innovation and workplace flexibility.

Benefits

• Eligible for an annual bonus incentive program.