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Junior Machine Learning Jobs in Delaware (NOW HIRING)

OneMain Financial

VP/MD Analytics

Wilmington, DE

Proven experience in assessing, mentoring, and developing junior data science talent * Advanced experience in use of open-source machine learning libraries (Python or R) in a cloud-based environment

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Junior Machine Learning information

What does a junior machine learning engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

What are the key skills and qualifications needed to thrive as a junior machine learning engineer?

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.

What types of projects and tasks can a junior machine learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

What is the difference between Junior Machine Learning vs Data Scientist?

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

What are the most commonly searched types of Machine Learning jobs in Delaware?

The most popular types of Machine Learning jobs in Delaware are:

What are popular job titles related to Junior Machine Learning jobs in Delaware?

For Junior Machine Learning jobs in Delaware, the most frequently searched job titles are:

What job categories do people searching Junior Machine Learning jobs in Delaware look for?

The top searched job categories for Junior Machine Learning jobs in Delaware are:

Junior Machine Learning jobs near you
Infographic showing various Junior Machine Learning job openings in Delaware as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

VP/MD Analytics

OneMain Financial

Wilmington, DE

Full-time

Posted yesterday

New

OneMain Financial rating

7.4

Company rating: 7.4 out of 10

Based on 102 frontline employees who took The Breakroom Quiz

118th of 151 rated financial services

Job description

The Role

We're seeking a data science leader and practitioner to dream, design, and build machine learning foundations to drive our exciting growth agenda. The VP/MD of Data Science will focus on building the foundational data science capabilities to enable the integration and growth of our emerging Auto Finance businesses. This role will partner closely with credit, operations, and business leaders of our legacy direct auto and recently acquired indirect auto programs. This leader will set the data science strategy, build a team, and create core data science use cases and capabilities to enable rapid growth.

Reporting to the Head of Data Science, this is a critical leadership position that requires key characteristics including the ability to partner and influence across stakeholders, apply strategic thinking, practical business problem solving, a forward leaning results focus, and team leadership and development. This is a rare and exciting opportunity to own the design and development of advanced machine learning capabilities spanning underwriting, marketing, operations, and risk, in a company which combines the best of FinTech and Banking.

This individual will be charged with both building the future while delivering impact in the present and must have both the skills and orientation to get "hands on" the keyboard, particularly in the early days. This leader must also have a strong model risk management orientation - skilled in using "black box" approaches, while remaining skeptical and continuously challenging the team.

Responsibilities

  • Collaborate, influence, and "bring along" business and technology leaders to maximize the impact of machine learning solutions in the auto finance businesses
  • Design and build the foundational data science practices and develop the decision making algorithms (using traditional regression models and machine learning algorithms) to enable rapid and sustained growth of auto finance lending
  • Research and develop new modeling techniques that will keep OneMain at the forefront of the industry
  • Research and develop with both traditional and non-traditional data sources (such as information from other industries, tax data, deposit data, demographic data, digital data) to find insights which can be used in models to keep at the forefront of the industry
  • Apply diverse statistical and machine learning techniques to analyze a variety of datasets to solve complex, unstructured business problems
  • Work with wide range of open-source tools to analyze and extract value from granular tradeline level granular data
  • Recruit, develop, and lead a high performing and high potential team of data scientists to conduct statistical analysis and develop profit-driven decision framework and risk strategies
  • Independently complete analyses, draw conclusions, and present results to all levels of leaders in order to influence business/strategy decision
  • Partner with technology leaders to build and evolve an advanced machine learning environment for auto finance
  • Effectively prioritize competing initiatives across direct reports; translate strategic priorities into individual/team initiatives and manage expectations
  • Collaborate with Model Risk, Legal, Compliance, Audit, and other risk management functions to ensure solutions are developed that meet expected standards and policies

Qualifications

  • Master's Degree in a quantitative discipline (Engineering, Statistics, Economics, Biostatistics, Physics, Computer Science, or related field); PhD preferred
  • 6+ years of progressively broader roles in model development and implementation experience; at least 4 of those years in consumer lending (credit card; unsecured loans; auto lending; or home equity); auto finance experience is a plus, but an enthusiasm and ability to rapidly learn a consumer lending asset class is more important
  • Expert experience designing, developing, and implementing machine learning solutions - must have experience developing and maintaining credit underwriting machine learning systems in a FCRA governed context
  • Applied experience in a variety of modeling techniques like bagging, boosting, NLP and so forth, as was feature engineering
  • Proven experience in communicating with stakeholders across all phases of machine learning modeling project, including validation, deployment, and ongoing monitoring
  • Proven experience in assessing, mentoring, and developing junior data science talent
  • Advanced experience in use of open-source machine learning libraries (Python or R) in a cloud-based environment
  • Experience in identifying and managing the risks of machine learning systems
  • Innovative and capable of developing creative solutions to complex, data-driven problems

OneMain Holdings, Inc. is an Equal Employment Opportunity (EEO) employer. Qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship status, color, creed, culture, disability, ethnicity, gender, gender identity or expression, genetic information or history, marital status, military status, national origin, nationality, pregnancy, race, religion, sex, sexual orientation, socioeconomic status, transgender or on any other basis protected by law.

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