Principal Data Scientist – Advanced Analytics
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Job Description
Principal Data Scientist leading experimentation, causal inference, machine learning, and Generative AI. Advancing Vericast’s data-driven solutions for banks and credit unions.
Responsibilities:
- Lead 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 methodologies for lift measurement, incrementality testing, and causal inference
- Establish experimentation standards, governance, and best practices
- Build a culture of experimentation and data-driven decision-making with stakeholders
- 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
- Lead hands-on model development, coding, testing, and production deployment
- Create and maintain robust data pipelines for data quality, integrity, and scalability
- Evaluate emerging technologies and analytical approaches
- Collaborate with Product, Marketing, Sales, IT, Risk, and Compliance teams to solve high-value business opportunities
- Translate business challenges into testable hypotheses and analytical solutions
- Present findings and recommendations to technical and executive audiences
- Serve as a subject matter expert on experimentation, analytics, AI, and machine learning
- Mentor and coach data scientists through technical guidance and best-practice sharing
Requirements:
- Master's degree in Statistics, Data Science, Computer Science, Economics, Mathematics, Engineering, or a related quantitative field required
- 8+ years of progressive experience in data science, analytics, or machine learning roles
- Significant hands-on experience working with large-scale data environments
- Experience leading or serving as a senior technical contributor on experimentation, measurement, and advanced analytics initiatives
- Experience translating complex business challenges into scalable analytical solutions
- Experience influencing senior stakeholders and partnering with cross-functional teams
- Deep expertise in marketing experimentation, A/B testing, multivariate testing, experimental design, metric development, and lift/incrementality measurement
- Strong background in causal inference, hypothesis testing, statistical modeling, and power analysis
- Hands-on experience developing and deploying Market Mix Models, Attribution Models, and Uplift Models
- Experience with Machine Learning, Large Language Models, Generative AI, and agent-based frameworks such as LangChain or LangSmith
- Expertise in clustering, classification, regression, neural networks, anomaly detection, recommendation engines, and predictive modeling
- Advanced programming skills in Python, Spark/PySpark, and SQL
- Experience with Databricks, Snowflake, or similar data lake environments
- Experience with AWS and Azure cloud environments
- Familiarity with Kubernetes, Docker, and Git
- Experience with data visualization and business intelligence tools; Tableau preferred
- Ability to thrive in ambiguous environments and manage multiple priorities
- Exceptional communication and storytelling skills
- Experience mentoring and providing technical leadership to data scientists and analytics professionals
- Strong analytical thinking, problem-solving capabilities, and attention to detail
- Proven success collaborating across Product, Marketing, Sales, IT, Risk, Compliance, and other business functions
Benefits:
- Annual bonus incentive program
- Workplace flexibility
- Equal Opportunity employer
- Disability accommodations during the selection process
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