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Credit Controller In Jobs in Philadelphia, PA (NOW HIRING)

Whether you're working in our four global Home Offices, Distribution Centers or Retail Stores-TJ ... credit union; cell phone discounts. Also, those who meet certain service or hours requirements are ...

Chief Executive Officer / Ownership Position Summary We are seeking an experienced Controller ... Maintain accurate financial records in accordance with Generally Accepted Accounting Principles ...

AR & AP Supervisor

Conshohocken, PA · On-site

$75K - $90K/yr

... credit across our distribution network. You'll lead a small team of two specialists, report to the Controller, and work hand-in-hand with the CFO to keep our books clean and our month-end close on ...

AR & AP Supervisor

Conshohocken, PA · On-site

$75K - $90K/yr

... credit across our distribution network. You'll lead a small team of two specialists, report to the Controller, and work hand-in-hand with the CFO to keep our books clean and our month-end close on ...

Showing results 41-60

Credit Controller In information

See Philadelphia, PA salary details

$50K

$91.7K

$152.4K

How much do credit controller in jobs pay per year?

As of Sep 9, 2026, the average yearly pay for credit controller in in Philadelphia, PA is $91,688.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,500.00 and $151,400.00 per year, depending on experience, location, and employer.

What is the difference between Credit Controller In vs Accounts Receivable Clerk?

AspectCredit Controller InAccounts Receivable Clerk
Required CredentialsRelevant finance certifications, experience in credit controlBasic finance or accounting qualifications, data entry skills
Work EnvironmentFinancial departments, credit management teamsFinance or accounting departments, clerical roles
Employer & Industry UsageUsed in industries with credit sales, finance firmsCommon in retail, wholesale, and service sectors
Search & Comparison IntentFocus on credit control responsibilities, credit managementFocus on accounts receivable, invoicing, and payments

The main difference is that a Credit Controller In manages credit limits, collections, and credit risk, while an Accounts Receivable Clerk handles invoicing, payment processing, and record keeping. Both roles are essential in financial operations but focus on different aspects of credit and payment management within organizations.

How much do credit controllers get paid?

Credit controllers typically earn a salary ranging from £20,000 to £30,000 per year, with experienced professionals or those in senior roles earning over £35,000. Compensation can vary based on location, industry, and level of experience, and some roles may include bonuses or commission based on collection performance.

What do you do as a credit controller?

A credit controller is responsible for managing a company's credit policies, monitoring customer accounts, and collecting payments to ensure timely cash flow. They often use accounting software and communicate with clients to resolve overdue invoices while maintaining good customer relationships.

What is the role of a credit controller?

A credit controller is responsible for managing a company's credit policies, monitoring customer accounts, and ensuring timely collection of outstanding payments. They analyze creditworthiness, set credit limits, and work to minimize bad debt while maintaining positive customer relationships, often using accounting software and financial analysis skills.

What cities near Philadelphia, PA are hiring for Credit Controller In jobs?

Cities near Philadelphia, PA with the most Credit Controller In job openings:

Vice President - Credit Risk Data Science, Business Banking Risk Modeling

Wilmington, DE • On-site

JPMorgan Chase & Co
Finance and Insurance • 10K+ employees

Full-time

Medical, Retirement

This job post has expired today. Applications are no longer accepted.


Key responsibilities

  • Lead the design, development, and governance of a scalable enterprise Risk Attribute Library, owning end-to-end attribute and model quality.

  • Partner with cross-functional teams to ideate, prototype, and productionize advanced feature engineering methods.

  • Build robust machine learning and deep learning models, including Transformer-based approaches, to predict customer behavior and optimize risk strategies.


JPMorgan Chase & Co. rating

7.9

Company rating: 7.9 out of 10

Based on 500 frontline employees who took The Breakroom Quiz

78th of 176 rated banks


Job description

Bring your expertise to JPMorgan Chase. As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks, and using your expert judgement to solve real-world challenges that impact our company, customers and communities. Our culture in Risk Management and Compliance is all about thinking outside the box, challenging the status quo and striving to be best-in-class.
As a Vice President - Credit Risk Data Science, Business Banking Risk Modeling, you will lead advanced feature engineering and machine learning initiatives that power customer analytics and credit risk decisioning across Chase sub-lines of business. You will own the end-to-end design and scaling of an enterprise Risk Attribute Library, ensuring feature quality, lineage, and reusability, while building and improving production-grade models that influence critical business decisions. Starting with a focus on the card business, you will extend solutions across the broader Chase portfolio and drive innovation using modern analytics, deep learning, and large language model enabled approaches.

Job Responsibilities:

  • Lead the design, development, and governance of a scalable enterprise Risk Attribute Library, owning end-to-end attribute and model quality.
  • Drive consistency, reliability, and reuse of features across customer lifecycles and Chase sub-lines of business through rigorous standards and reproducible development practices.
  • Partner with cross-functional teams to ideate, prototype, and productionize advanced feature engineering methods.
  • Engineer high-impact features from large-scale structured and unstructured datasets to improve predictive performance and decisioning outcomes.
  • Build robust machine learning and deep learning models, including Transformer-based approaches, to predict customer behavior and optimize risk strategies.
  • Apply large language model techniques to extract signal from unstructured text (for example, customer interactions, disclosures, narratives) to enhance models and enable new analytics products.
  • Establish attribute quality testing and monitoring frameworks to detect data drift, leakage, instability, and distribution shifts.
  • Implement alerting mechanisms and resolve data or feature issues to maintain accuracy, stability, and consistency in production.
  • Evaluate new internal and external data sources by assessing signal strength, stability, latency, and compliance considerations.
  • Align with risk, marketing, technology, data governance, and controls partners to ensure correct implementation and robust documentation, lineage, and lifecycle management.
  • Communicate complex analytical findings clearly to technical and non-technical stakeholders, translating results into actionable recommendations and measurable business impact.
     

Required Qualifications, Capabilities, and Skills:

  • Master's degree or Doctor of Philosophy degree in Computer Science, Mathematics, Statistics, Econometrics, Engineering, or a related quantitative discipline.
  • 5+ years of experience working with large-scale data and developing, managing, or implementing attributes and predictive models.
  • 5+ years of professional coding experience with demonstrated ability to write high-quality, production-ready code.
  • Proficiency in one or more of the following: Python, Statistical Analysis System, Apache Spark, Scala, or equivalent data and machine learning programming stacks.
  • Experience with modern machine learning and deep learning frameworks and platforms such as TensorFlow (or equivalent), Amazon Web Services cloud, Snowflake, and or Databricks.
  • Strong understanding of statistical and machine learning methods such as generalized linear models and regression, decision trees, random forests, boosting, clustering, k-nearest neighbors, anomaly detection, simulation, scenario analysis, and modeling.
  • Demonstrated ability to perform feature engineering, model validation, and performance evaluation in a regulated or controlled environment.
     

Preferred Qualifications, Capabilities, and Skills:

  • consumer lending experience strongly preferred

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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