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Data Science Assistant Jobs (NOW HIRING)

campus4tech

Data Scientist

Manhattan, NY · On-site

Leverage GenAI/Data Assist tools to accelerate data science workflows. * Collaborate with stakeholders to align models with business outcomes. * Build and refine machine learning models under ...

Equation Staffing

VP of Data Science

Manhattan, NY

VP Data Science As the VP of Data Science, you'll play a critical role in building a data-driven ... assist with data-related technical issues and support their data infrastructure needs. · Manage ...

AEVEX

Program Data Science Analyst

Tampa, FL

This role blends deep data science expertise with program analysis, enabling the organization to ... * Assist in budget tracking, cost analysis, and resource allocation planning to help ensure ...

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Data Science Assistant information

What are Data Science Assistants?

Data Science Assistants are professionals who support data scientists and analytics teams by handling tasks such as data collection, data cleaning, preparing datasets, conducting preliminary analyses, and creating visualizations. They often work with large datasets, assist in maintaining data integrity, and help automate routine processes. Their role allows data scientists to focus on more complex modeling and analytical work, making the overall workflow more efficient. Data Science Assistants typically have a foundational understanding of statistics, programming (such as Python or R), and data management tools.

What are the key skills and qualifications needed to thrive as a Data Science Assistant, and why are they important?

To thrive as a Data Science Assistant, you need a solid understanding of statistics, data analysis, and programming (often with a background in mathematics, computer science, or a related field). Familiarity with tools like Python or R, data visualization software, and experience with databases or spreadsheet systems are typically required. Attention to detail, strong problem-solving abilities, and effective communication set outstanding candidates apart. These skills are crucial for supporting data-driven decision-making and ensuring accurate, actionable insights for organizations.

Is 40 too late for data science?

Data Science Assistants and other data science roles do not have strict age limits; many professionals start or transition into data science later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned at any age through online courses, certifications, and practical experience.

How does a Data Science Assistant typically collaborate with data scientists and other team members on projects?

As a Data Science Assistant, you will frequently support data scientists by preparing datasets, conducting preliminary data analysis, and creating visualizations. You will often work closely with analysts, engineers, and subject matter experts to gather requirements and ensure data is cleaned and formatted appropriately. Collaboration is a key part of the role, as you may participate in team meetings, share findings, and help with documentation to keep projects running smoothly. This supportive environment provides an excellent opportunity to learn from experienced professionals and gain exposure to the full data science workflow.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of the results come from 20% of the efforts or data. Data scientists often use this concept to focus on the most impactful features, data subsets, or tasks to improve model performance efficiently.

What is the difference between Data Science Assistant vs Data Analyst?

AspectData Science AssistantData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related fieldBachelor's in Statistics, Mathematics, or related field
Work EnvironmentTech companies, research labs, data-driven departmentsBusiness, finance, marketing, healthcare sectors
Employer & Industry UsageUsed in data science teams for supporting models and analysisUsed across industries for interpreting data and generating reports

While both roles involve working with data, a Data Science Assistant typically supports data science projects, focusing on data preparation and model testing. A Data Analyst primarily interprets data to generate insights and reports. The roles overlap in skills and work environments but differ in their core responsibilities and focus areas.

What do data assistants do?

Data Science Assistants support data analysis by collecting, cleaning, and organizing data sets. They often use tools like Excel, SQL, or Python to prepare data for modeling and reporting, assisting data scientists and analysts in project workflows.

Can I get a data scientist job with no experience?

Entry-level data science assistant roles often do not require prior experience, but candidates typically need a strong foundation in programming (such as Python or R), statistics, and data analysis. Gaining relevant skills through online courses, certifications, or personal projects can improve chances of securing such positions.
More about Data Science Assistant jobs
What cities are hiring for Data Science Assistant jobs? Cities with the most Data Science Assistant job openings:
What are the most commonly searched types of Data Science jobs? The most popular types of Data Science jobs are:
What states have the most Data Science Assistant jobs? States with the most job openings for Data Science Assistant jobs include:
What job categories do people searching Data Science Assistant jobs look for? The top searched job categories for Data Science Assistant jobs are:
Data Science Assistant jobs near you
Infographic showing various Data Science Assistant job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 99% Physical, and 1% Remote job distribution.

Data Scientist

campus4tech

Manhattan, NY • On-site

Full-time

Posted 25 days ago

Job description

Job Title- Data Scientist
Location- New York, NY 10112
Reporting Type- Onsite
W2 candidates only preferred
Green Card Holders and US Citizens only preferred
Summary
This role involves building and delivering advanced data science and AI/ML solutions in an agile environment, with a focus on rapid iteration and business impact. The Data Science Lead will drive end-to-end model development, including propensity modeling and integration with data engineering pipelines, while leveraging GenAI to accelerate outcomes. Supporting roles include Data Scientists and Data Engineers who will collaborate to build models, manage data pipelines, and ensure scalable data infrastructure. Experience in the HR domain is a plus.
Responsibilities
  • Lead end-to-end data science projects using agile and iterative approaches.
  • Develop and deploy AI/ML models, including propensity modeling.
  • Drive data engineering requirements to support model development and optimization.
  • Leverage GenAI/Data Assist tools to accelerate data science workflows.
  • Collaborate with stakeholders to align models with business outcomes.
  • Build and refine machine learning models under guidance.
  • Perform data analysis, feature engineering, and model validation.
  • Support deployment and testing of AI/ML solutions.

Requirements
  • Data Science Lead (SC or M level) - should have experience leading data science projects with rapid iterations in an agile manner.
  • Should have experience developing AI/ML propensity modeling experience and in driving data engineering to support the model development and refinement.
  • Driving the use of Data Assist or GenAI to accelerate the project would be great. Experience in the HR domain would be ideal!
    Data Science Support (SC or C level) - Should have AI/ML experience and be able to take direction and develop model as part of a team

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