We are seeking a highly skilled and experienced Collections Analytics Manager to
join our dynamic team supporting a leading credit card client. The ideal
candidate will be responsible for developing, implementing, and optimizing
collections strategies across the delinquency lifecycle to minimize credit
losses and manage cost-to-collect, while balancing customer experience and
regulatory compliance.
Work Location: Remote, US
Salary Range: $130K/Yr - $150K/Yr Base + Annual Bonus
The posted range is the hiring range for this role — a subset of the broader
range available to employees over time — and reflects base salary across our
national hiring scale. Final offers are based on several factors, including the
candidate's skills and experience, internal pay equity, work location, market
conditions for the role, and the specific scope and responsibilities of the
position. The top of the range is reserved for candidates who notably exceed the
requirements; the lower end applies to those with less experience or fewer
preferred qualifications. For positions based in higher-cost zones (e.g.,
California, New York, New Jersey), actual compensation may exceed the posted
range; your recruiter will share specifics during the process
For more information on benefits and what we offer please visit us at US Careers
and Benefits
RESPONSIBILITIES
Develop and implement collections strategies across all stages of delinquency
(early-stage, mid-stage, late-stage, and pre-charge-off) by collaborating
with cross-functional stakeholders, including Collections Operations, Credit
Risk, Regulatory/Compliance, Product, Finance, and Analytics teams, ensuring
alignment with business objectives and compliance requirements.
Design and optimize risk-based treatment strategies, including customer
segmentation and prioritization, contact channel mix (dialer, SMS, email,
digital self-service, letters), contact timing and intensity, and hardship,
payment plan, and settlement offers.
Conduct end-to-end data analysis across the collections funnel, including
roll rates, cure rates, flow-to-loss, right-party contact rates,
promise-to-pay and kept-promise rates, dollars collected, and
cost-to-collect, to identify risks, opportunities, and performance
improvement areas.
Design, execute, and evaluate champion/challenger and A/B tests on
collections treatments; measure incremental impact and scale winning
strategies.
Partner with modeling teams to develop, deploy, and monitor collections
models such as behavior scores, propensity-to-pay, self-cure, and settlement
propensity models, and embed them into strategy design.
Monitor and track portfolio delinquency and charge-off performance metrics;
analyze emerging trends and macroeconomic stress indicators; and recommend
strategic enhancements to optimize net credit losses and risk-adjusted
returns.
Support delinquency and charge-off forecasting in partnership with Finance
and Loss Forecasting teams.
Partner with Collections Operations on dialer strategy, agency placement
strategy, and capacity planning, translating analytical strategies into
operational execution.
Present analytical insights and strategic recommendations to senior
leadership, driving consensus through governance forums and securing
approvals for policy and strategy implementation.
QUALIFICATIONS
Educational Background: Bachelor's or higher degree in engineering,
statistics, mathematics, economics, or any relevant quantitative field.
Industry Experience: Minimum of 6 years of experience in credit risk or
collections analytics, with a focus on collections strategy development for
credit cards or other unsecured lending products. Previous experience in
analytics consulting in the Banking domain.
Domain Knowledge: Strong understanding of the credit card collections
lifecycle, delinquency buckets and roll-rate dynamics, charge-off policies,
and agency management.
Technical Skills: Strong proficiency in SQL or Python is essential.
Preference for hands-on experience with Snowflake, Power BI, and Looker.
Familiarity with collections platforms, dialer systems, and decision engines
is a plus.
Analytical Skills: Strong analytical and problem-solving skills. Past
experience in statistical analysis, test design and measurement,
segmentation, and financial modeling, including NPV-based evaluation of
collections strategies.
Communication Skills: Strong communication and interpersonal skills, with the
ability to collaborate effectively with stakeholders at all levels.
Experience in working with financial institutions such as bank or fintech
collections or risk analytics departments.