Sr. Specialist, Advanced Analytics

The Sr. Specialist, Advanced Analytics is a seasoned expert in statistical modeling, machine learning, and predictive analytics who operates with a high degree of autonomy to design, build, and deploy sophisticated analytical solutions that drive measurable business outcomes. This role owns the end-to-end lifecycle of advanced models — including customer lifetime value, churn prediction, propensity modeling, and advanced segmentation — and serves as a trusted analytical advisor to business stakeholders and senior leadership.

The Sr. Specialist is expected to bring deep technical mastery combined with strong business judgment, translating ambiguous business problems into well-defined analytical frameworks and translating complex model outputs into clear, actionable strategic recommendations. This individual also plays a key role in elevating the capability of the broader analytics team through mentorship, best-practice development, and technical leadership.

• Lead the full analytical project lifecycle — from problem framing and data exploration through model development, validation, deployment, and ongoing performance monitoring.

• Partner directly with business stakeholders and cross-functional leaders to identify high-value analytical opportunities, scope projects, and align modeling approaches with strategic business objectives.

• Translate complex statistical and machine learning outputs into clear, non-technical narratives and actionable recommendations for executive and business audiences.

• Proactively identify data quality issues, model drift, or emerging risks in production models and lead remediation efforts.

• Independently design, develop, and deploy advanced predictive and machine learning models (e.g., customer lifetime value, churn, propensity-to-buy, next-best-action, advanced segmentation) with minimal oversight.

• Establish and maintain model governance practices, including documentation, validation standards, and monitoring frameworks to ensure models remain accurate and reliable in production.

• Mentor and coach junior and mid-level analysts on statistical techniques, coding best practices, model validation methods, and business communication skills.

• Lead or significantly contribute to large, cross-team analytical initiatives, often coordinating work across multiple contributors and stakeholders.

• Stay current on emerging Snow Flake, SQL, Databricks, emerging AI and machine learning techniques, tools, and industry best practices, and champion their adoption where relevant.

• Collaborate with data engineering and IT teams to ensure analytical infrastructure, data pipelines, and tooling support scalable model development and deployment.

• Present findings, methodologies, and business impact to senior leadership and various cross-functional partners.

• Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, Economics, or a related quantitative field required;
  Master's degree or equivalent experience preferred.

• 3 – 5 years of progressive experience in statistical modeling, predictive analytics, or data science, with a demonstrated track record of independently delivering complex analytical solutions.

• Advanced, demonstrated expertise in machine learning algorithms (e.g., gradient boosting, random forests, clustering, survival analysis) and statistical modeling techniques.

• Expert-level proficiency in R and/or Python, with strong SQL skills; experience with cloud-based or enterprise analytical infrastructure strongly preferred.

• Proven experience building and deploying customer lifetime value, churn, and segmentation models in a production business environment.

• Strong business acumen with the demonstrated ability to translate…