Sr. Performance Strategist, Collections

We are seeking a highly analytical Senior Performance Strategist to optimize collections performance across a large-scale, AI-powered debt recovery platform. In this role, you will investigate performance trends, uncover root causes, and translate complex data into actionable strategies that improve recovery rates, customer engagement, and client outcomes. You will collaborate with data scientists, strategy leaders, and cross-functional teams to identify opportunities, resolve technical issues, and enhance decision-making. Through advanced analytics, forecasting, and structured experimentation, you will help shape strategies that deliver measurable financial impact. You will also contribute to revenue planning and communicate clear, evidence-based recommendations to clients and senior leadership. This remote opportunity is ideal for a curious, data-driven professional who thrives in a fast-paced environment and enjoys solving complex business and technical challenges.

• Professional experience: At least six years of experience in analytics, particularly in performance diagnosis, funnel or lifecycle analysis, cohort analysis, performance curve evaluation, or channel optimization. Relevant backgrounds may include consumer collections, lending, customer relationship management (CRM), subscription businesses, or e-commerce.

• Education: Bachelor's degree in a quantitative field or equivalent practical experience.

• Advanced SQL skills: Proven ability to independently query complex data structures, navigate large datasets, and build custom analytical datasets using platforms such as Snowflake.

• Technical investigation: Ability to read and trace Python code, configuration files, business rules, or system logic to understand application behavior and identify the causes of performance changes. Production software development experience is not required.

• Analytical problem-solving: Strong diagnostic instincts and the ability to distinguish correlation from causation, test competing explanations, and identify the underlying drivers of complex business problems.

• Forecasting and experimentation: Experience developing reliable forecasts, scenario models, and what-if analyses, with a working understanding of statistical significance, hypothesis testing, and experimental design.

• Business intelligence: Proficiency with self-service analytics and visualization tools such as Looker or Tableau, along with the ability to turn complex datasets into clear, decision-ready insights.

• AI proficiency: Practical experience using AI tools regularly to improve analytical productivity, accelerate data exploration, and generate insights.

• Communication and collaboration: Excellent written and verbal communication skills, with the ability to explain technical findings to both technical and non-technical audiences and influence decisions across multiple teams.

• Preferred qualifications: Experience with machine learning decision engines, champion/challenger testing methodologies, system log analysis, or other techniques used to evaluate and optimize automated decision-making systems.

• Working arrangements: Ability to work effectively in a remote-first environment, maintain a reliable internet connection, protect confidential information, and accommodate occasional schedule flexibility or travel for team meetings, training, and collaborative projects.