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 ...
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 ...
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 ...
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 ...
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Sr Lead Security Engineer
Wilmington, DE · On-site
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Design and implement enterprise-grade Machine Learning platforms capable of deploying and running ... partners, and senior leadership. * Deliver high-quality results within tight deadlines while ...
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Quick apply
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CCB Risk Program Associate
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CCB Risk Program Associate
Wilmington, DE · On-site
$57K - $57K/yr
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Senior Machine Learning Engineer information
See New Castle, DE salary details
$57.5K - $68.4K
1% of jobs
$68.4K - $79.3K
3% of jobs
$79.3K - $90.2K
7% of jobs
$100.9K is the 25th percentile. Wages below this are outliers.
$90.2K - $101.1K
14% of jobs
$101.1K - $112K
17% of jobs
The median wage is $116.6K / yr.
$112K - $122.9K
19% of jobs
$122.9K - $133.8K
13% of jobs
$135.2K is the 75th percentile. Wages above this are outliers.
$133.8K - $144.7K
11% of jobs
$144.7K - $155.6K
7% of jobs
$155.6K - $166.5K
5% of jobs
$166.5K - $177.4K
3% of jobs
$57.5K
$122.4K
$177.4K
How much do senior machine learning engineer jobs pay per year?
What does a senior machine learning engineer do?
What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?
What are the key skills and qualifications needed to thrive as a senior machine learning engineer, and why are they important?
What is the difference between Senior Machine Learning Engineer vs Data Scientist?
| Aspect | Senior Machine Learning Engineer | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's/Master's in CS, ML, or related; experience with ML frameworks | Bachelor's/Master's in CS, Statistics, or related; strong analytical skills |
| Work Environment | Develops and deploys ML models in production systems | Analyzes data, builds models, and provides insights |
| Industry Usage | Tech, finance, healthcare, e-commerce | Research, finance, marketing, tech |
While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.
What cities near New Castle, DE are hiring for Senior Machine Learning Engineer jobs?
Cities near New Castle, DE with the most Senior Machine Learning Engineer job openings:

Vice President - Credit Risk Data Science, Business Banking Risk Modeling
Wilmington, DE • On-site
Full-time
Medical, Retirement
Posted 9 days ago
JPMorgan Chase & Co. rating
8.0
Based on 499 frontline employees who took The Breakroom Quiz
72nd of 174 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
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Pay
Benefits
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About JPMorgan Chase & Co
Sourced by ZipRecruiter
Industry
Finance and insurance and banking and credit intermediation
Company size
10,000+ Employees
Headquarters location
New York, NY, US