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Associate Data Modeler Jobs (NOW HIRING)

Quantifind

Associate Data Scientist

$60K - $60K/yr

They are seeking an Associate Data Scientist to collaborate with teams to analyze large datasets, train machine learning models, and implement solutions in a fast-paced startup environment.

Capital One

Senior Associate, Data Science

Mclean, VA · On-site

Senior Associate, Data Science Data is at the center of everything we do. As a startup, we ... We partner with model development and software engineering teams to build predictive models and ...

Capital One

Senior Associate, Data Science

Mclean, VA · On-site

Senior Associate, Data Science Data is at the center of everything we do. As a startup, we ... We partner with model development and software engineering teams to build predictive models and ...

Capital One

Senior Associate, Data Science

Mclean, VA · On-site

Senior Associate, Data Science Data is at the center of everything we do. As a startup, we ... We partner with model development and software engineering teams to build predictive models and ...

Capital One

Senior Associate, Data Science

Mclean, VA · On-site

Senior Associate, Data Science Data is at the center of everything we do. As a startup, we ... We partner with model development and software engineering teams to build predictive models and ...

Capital One

Senior Associate, Data Science

Mclean, VA · On-site

Senior Associate, Data Science Data is at the center of everything we do. As a startup, we ... We partner with model development and software engineering teams to build predictive models and ...

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Associate Data Modeler information

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How much do associate data modeler jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for associate data modeler in the United States is $58.71, according to ZipRecruiter salary data. Most workers in this role earn between $52.64 and $68.27 per hour, depending on experience, location, and employer.

What is an associate data modeler?

An Associate Data Modeler is an entry-level professional who assists in designing, creating, and maintaining data models that define how data is structured and used within an organization. They work closely with senior data modelers, database administrators, and business analysts to ensure data models accurately reflect business needs and support data integrity. Responsibilities often include developing entity-relationship diagrams, documenting data definitions, and helping to translate business requirements into technical specifications. This role is important in supporting data-driven decision making and efficient database design.

What is the difference between Associate Data Modeler vs Data Analyst?

AspectAssociate Data ModelerData Analyst
Required CredentialsBachelor's in CS, IT, or related field; familiarity with data modeling toolsBachelor's in Statistics, Math, or related; proficiency in data analysis tools
Work EnvironmentData teams, IT departments, database environmentsBusiness units, reporting teams, data visualization settings
Employer & Industry UsageTech, finance, healthcare, and data-driven industriesMarketing, finance, healthcare, and business sectors

The Associate Data Modeler focuses on designing and maintaining data structures and models, working closely with database systems. In contrast, a Data Analyst interprets data, creates reports, and provides insights. While both roles require data-related skills, the Associate Data Modeler emphasizes data architecture, whereas the Data Analyst emphasizes data interpretation and reporting.

What are the key skills and qualifications needed to thrive as an associate data modeler, and why are they important?

To thrive as an Associate Data Modeler, you need a solid understanding of database design principles, data analysis, and proficiency in SQL, often supported by a degree in computer science or a related field. Familiarity with data modeling tools like ERwin, Microsoft Visio, or IBM InfoSphere, as well as knowledge of relational database management systems (RDBMS), is typically required. Strong analytical thinking, attention to detail, and effective communication skills help you interpret business requirements and collaborate with technical teams. These competencies ensure accurate data representation, efficient database structures, and alignment with organizational data needs.

What are some typical projects or tasks that an associate data modeler might work on in the first year?

As an Associate Data Modeler, you can expect to support senior data modelers and data architects in designing, developing, and maintaining data models for various business applications. Typical projects include translating business requirements into logical and physical data models, normalizing data structures, and assisting in data mapping or integration efforts. You may also participate in data governance initiatives, review existing data models for optimization, and collaborate with cross-functional teams such as business analysts, database developers, and IT staff. These experiences will help you build a strong foundation for more advanced data architecture roles in the future.
More about Associate Data Modeler jobs
What cities are hiring for Associate Data Modeler jobs? Cities with the most Associate Data Modeler job openings:
What are the most commonly searched types of Data Modeler jobs? The most popular types of Data Modeler jobs are:
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Associate Data Modeler jobs near you
Infographic showing various Associate Data Modeler job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $122,123 per year, or $58.7 per hour.

Associate Data Scientist

Quantifind

Remote

$60K - $60K/yr

Full-time

Re-posted 3 days ago

Job description

Job Summary:
Quantifind is a data science technology company that helps major banks combat money laundering and fraud. They are seeking an Associate Data Scientist to collaborate with teams to analyze large datasets, train machine learning models, and implement solutions in a fast-paced startup environment.
Responsibilities:
• Collaborating with fellow team members and key stakeholders, such as, Product Managers, Platform Engineers to explore ideas, test hypotheses, and prototype solutions.
• Working in an agile environment breaking down complex problems into smaller manageable tasks with the help of your teammates and manager.
• Leveraging SQL, Python and PySpark to analyze large unstructured data sets to answer key business questions, inform next steps or set up modeling tasks.
• Writing complex pipeline code often involving NLP enrichment steps to process large data sets.
• Training machine learning models to solve complex problems.
• Productionizing models in a Scala codebase following software engineering best practices.
• Validating models using standard and custom performance metrics.
• Leveraging Large Language Models (LLMs) to scale up various data science tasks (for example: data labeling, extracting structured information, …)
• Participating in code reviews.
Qualifications:
Required:
• MS or higher in the following areas: Statistics, Mathematics, or Computer Science
• At least 1 year of professional industry experience, in addition to your academic experience
• Outstanding analytical skills and the ability to communicate quantitative results to technical and non-technical audiences
• Strong knowledge of Statistics/Probability/Machine Learning including core concepts of hypothesis testing, inference, bias-variance trade-off, regularization, dimensionality reduction etc.
• Supervised and unsupervised statistical techniques such as regression, classification, and clustering
• Experience with popular machine learning algorithms such as random forests, Boosting, and neural networks
• Strong programming experience in Python and one or more of the following: Scala/Java or R
• Experience with SQL and/or Spark
• Knowledge of data structures and algorithm complexity
Preferred:
• Experience with Applied NLP methods such as topic modeling, text classification, word embeddings, and named entity extraction is a strong plus
Company:
Quantifind is a risk intelligence company that offers AI solutions for emerging threat detection and watchlist screening. Founded in 2009, the company is headquartered in Palo Alto, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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