Sr. Performance Strategist, Collections in United States at Jobgether

Diagnose performance trends: Monitor key performance indicators across clients, portfolios, and communication channels, distinguishing external market influences from internal operational factors to identify emerging risks and opportunities before they affect recovery outcomes.

Investigate root causes: Analyze performance fluctuations beyond standard reporting by tracing application logic, business rules, system configurations, and processing workflows to uncover technical defects, strategy gaps, and other underlying issues.

Develop and execute optimization strategies: Translate analytical findings into clear, prioritized recommendations with expected business impacts and measurable success criteria, partnering with strategy leadership to implement improvements in production.

Lead forecasting and scenario modeling: Conduct what-if analyses, stress tests, and revenue forecasts to support business planning and evaluate the financial implications of changes in client portfolios, account placements, and collection strategies.

Design and evaluate experiments: Develop testable hypotheses, establish decision thresholds, and analyze structured experiments to determine which strategies should be scaled, refined, or discontinued.

Support client relationships: Work closely with Client Managers to develop accurate, defensible performance narratives, challenge unsupported assumptions, and participate in important client discussions when analytical expertise is needed.

Leverage data and AI tools: Use advanced SQL, business intelligence platforms, and AI-assisted analytical workflows to accelerate investigations, improve insight generation, and support evidence-based decision-making.

Collaborate across teams: Partner with Strategy, Data Science, Engineering, and Product teams to communicate findings, resolve performance issues, and ensure analytical recommendations translate into measurable operational and financial improvements.

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.

Competitive compensation: Annual base salary ranging from $120,000 to $170,000, depending on geographic labor market, skills, experience, and qualifications.

Flexible vacation: Flexible paid vacation to support work-life balance and personal well-being.

Healthcare coverage: Medical, dental, and vision insurance.

Retirement savings: Traditional and Roth retirement savings options.

Insurance protection: Company-paid disability and life insurance.

Flexible spending accounts: Access to Flexible Spending Accounts (FSA) and Limited Purpose FSA options.

Family-friendly leave: Parental leave, along with paid time off for volunteering and voting.

Wellness resources: Access to an on-demand wellness platform for employees and up to five friends or family members.

Employee discounts: Access to the PerkSpot discount program, featuring offers from more than 900 merchants nationwide.

Remote-first work environment: The flexibility to work remotely while collaborating with colleagues across a global, cross-functional organization.

Professional growth: Opportunities to develop analytical expertise, contribute to innovative AI-driven strategies, and work on high-impact business challenges.