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Temporary Data Scientist Machine Learning Jobs (NOW HIRING)

Partner directly with quantitative researchers to understand the needs of a specific machine learning project and collaboratively produce data that best fits the model and project * Transform raw ...

DATA SCIENTIST

San Diego, CA · On-site

$120K - $150K/yr

iQuasar is seeking to fill an Data Scientist/Machine Learning Engineerin San Diego, CA. At iQuasar, we strive to provide the next generation of cutting-edge technologies. Our growth means exciting ...

DATA SCIENTIST

San Diego, CA · On-site

$120K - $150K/yr

iQuasar is seeking to fill an Data Scientist/Machine Learning Engineerin San Diego, CA. At iQuasar, we strive to provide the next generation of cutting-edge technologies. Our growth means exciting ...

No As the Senior Data Scientist for Machine Learning supporting the Healthcare Fraud Prevention Partnership (HFPP), you will be the first dedicated machine learning practitioner at the Trusted Third ...

So what's the job As a Senior Machine Learning Data Scientist in the Data Team at Catawiki you will focus on delivering scalable and impactful data products. You'll work closely with our product and ...

Move fast, learn fast: hundreds of experiments run monthly; rigorous experimentation culture Why this Role is Different Most Data Science roles currently on the market are focused on optimizing ad ...

Data Scientist / Machine Learning Engineer Position Overview As a Data Scientist / Machine Learning Engineer on our AI Builder program, you will design, develop, and operationalize advanced analytics ...

Hybrid onsite Tuesday Wednesday and Thursday Data Scientist / Machine Learning Engineer Position Overview As a Data Scientist / Machine Learning Engineer on our AI Builder program, you will design ...

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Temporary Data Scientist Machine Learning information

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$37.5K

$122.7K

$196.5K

How much do temporary data scientist machine learning jobs pay per year?

As of Sep 5, 2026, the average yearly pay for temporary data scientist machine learning in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What does a temporary data scientist specializing in machine learning do?

A Temporary Data Scientist specializing in Machine Learning is responsible for designing, building, and deploying machine learning models to analyze data and generate insights, but works on a contract or short-term basis. Their duties often include data preprocessing, model selection and validation, and communicating results to stakeholders. They may also be tasked with automating processes, cleaning large datasets, and collaborating with other teams to implement solutions. The temporary nature of the job means they often focus on specific projects or provide support during peak periods.

What are the key skills and qualifications needed to thrive as a temporary data scientist specializing in machine learning?

To thrive as a Temporary Data Scientist Machine Learning, you generally need a strong background in statistics, programming (Python or R), and experience with machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with data visualization tools (like Tableau), machine learning libraries (such as scikit-learn, TensorFlow, or PyTorch), and version control systems (e.g., Git) is typically required. Strong problem-solving abilities, adaptability, and effective communication are crucial soft skills for collaborating with teams and translating technical findings to stakeholders. These skills ensure that temporary data scientists can quickly contribute actionable insights, drive data-driven decisions, and add value within a limited time frame.

What are some typical projects or tasks a temporary data scientist specializing in machine learning might work on?

As a temporary Data Scientist focusing on machine learning, you can expect to work on short-term, high-impact projects such as building predictive models, cleaning and preparing data, or developing automated analytics solutions. You may be brought in to support ongoing initiatives, provide expertise for a specific project phase, or help accelerate a backlog of tasks. Collaboration is common, and you'll likely work closely with data engineers, business analysts, and domain experts to understand requirements and deliver actionable insights within tight deadlines. This role offers exposure to diverse datasets and tools, and is an excellent opportunity to rapidly expand your experience and network.

What is the difference between Temporary Data Scientist Machine Learning vs Temporary Data Analyst?

AspectTemporary Data Scientist Machine LearningTemporary Data Analyst
Required CredentialsBachelor's/Master's in Data Science, Computer Science, or related fields; knowledge of ML algorithmsBachelor's in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentProject-based, collaborative teams, tech-focused companiesBusiness units, reporting teams, data-driven departments
Employer & Industry UsageTech firms, finance, healthcare, e-commerceRetail, marketing, finance, consulting

Temporary Data Scientist Machine Learning roles focus on developing and deploying machine learning models, requiring advanced analytics skills. Temporary Data Analysts primarily interpret data, generate reports, and support decision-making. While both roles involve data handling, Data Scientists with ML expertise work on predictive modeling, whereas Data Analysts focus on descriptive analytics. The choice depends on the project needs and skill requirements.

More about Temporary Data Scientist Machine Learning jobs

What cities are hiring for Temporary Data Scientist Machine Learning jobs?

Cities with the most Temporary Data Scientist Machine Learning job openings:

What are the most commonly searched types of Data Scientist Machine Learning jobs?

The most popular types of Data Scientist Machine Learning jobs are:

What states have the most Temporary Data Scientist Machine Learning jobs?

States with the most job openings for Temporary Data Scientist Machine Learning jobs include:

Infographic showing various Temporary Data Scientist Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist, Machine Learning

AQR

Greenwich, CT

$180K - $200K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 5 days ago


Key responsibilities

  • Partner with researchers to understand project data needs and produce suitable datasets and features.

  • Transform raw data into research-ready, project-specific datasets and perform feature generation.

  • Build data quality assurance, monitoring, and profiling workflows to ensure datasets are clean, traceable, and reliable.


Job description

About AQR Capital Management

AQR is a global investment management firm built at the intersection of financial theory and practical application. We strive to deliver superior, long-term results for our clients by seeking to filter out market noise to identify and isolate what matters most, and by developing ideas that stand up to rigorous testing. Underpinning this philosophy is an unrelenting commitment to excellence in technology - powering our insights and analysis. This unique combination has made us leaders in alternative and traditional strategies since 1998.

AQR takes a systematic, research-driven approach, applying quantitative tools to process fundamental information and manage risk. Our clients include institutional investors, such as pension funds, insurance companies, endowments, foundations and sovereign wealth funds, as well as financial advisors.

Your Role:

You will serve as a bridge between data engineering and quantitative research. Working directly with researchers, you will also be responsible for ensuring research datasets are accurate, traceable, and ready for machine learning by developing robust data preparation and quality workflows. Your responsibility is to deliver clean, reliable, project-specific datasets and features to the researcher. 

What You'll Do:

  • Partner directly with quantitative researchers to understand the needs of a specific machine learning project and collaboratively produce data that best fits the model and project
  • Transform raw structured and unstructured data into project-specific, research-ready datasets
  • Perform feature generation and deliver prepared datasets and features to the researcher for modeling and productionization
  • Resolve tagging, entity-matching, and linkage issues across signals, textual data, and securities
  • Build data quality assurance, quality monitoring, and profiling workflows through programmatic checks, LLM reviews where appropriate, targeted manual inspection, and feedback-driven iterative refinement
  • Build point-in-time mappings and knowledge graphs for mergers and acquisitions, bankruptcies, IPOs, and other corporate events
  • Examine and onboard alternative datasets
  • Ensure datasets are clean, traceable, and reliable for trading strategies
  • Work across different researchers and potentially concurrent projects as priorities and the scope of the role evolve
  • Communicate clearly with researchers and engineering partners

What You'll Bring:

  • 4+ years of relevant work experience
  • Strong Python programming skills, including hands-on experience with pandas and NumPy
  • Strong SQL skills and practical experience with PostgreSQL
  • Experience working with both structured data and unstructured or textual data
  • Experience with data quality, validation, monitoring, and profiling
  • Experience with Git, PyTest, CI/CD, and API development
  • Ability to reason carefully through edge cases, protect data integrity, and maintain clear documentation of data definitions, transformations, and quality checks
  • Ability to work independently, communicate clearly with technical and non-technical stakeholders, and manage work across multiple concurrent initiatives
  • Strong visualization skills

Preferred Qualifications:

  • Experience with scikit-learn, statistics, or advanced modeling techniques
  • Experience with entity resolution, entity matching, or knowledge graphs
  • Experience designing prompts and using LLM APIs for batched or large-scale investigation, validation, feature generation, and iterative refinement
  • Experience building LLM-based featurization workflows, including iterative refinement, validation, and automated testing
  • Experience with Claude Code, Codex, or AWS Bedrock
  • Experience with AWS, including S3 and Batch
  • Experience with distributed computing and large-scale data processing
  • Exposure to data governance, data cataloging, or related best practices
  • Strong Math and statistics skills
  • Experience with Pytorch
  • Prior experience in financial services, trading, quantitative research, or another research-driven environment

 Who You Are:

  • Rigorous, thorough, and highly attentive to detail
  • Collaborative and able to communicate effectively with researchers and engineering partners
  • Comfortable working in an evolving role and taking on a broad range of responsibilities

AQR is an Equal Opportunity Employer. EEO/VET/DISABILITY

The salary range for this role is expected to be $180,000 to $200,000.  This is the range that we in good faith believe is accurate for this role at the time of this posting.  We may ultimately pay more or less than the posted range, depending upon factors such as skills, experience, location, or other business and organizational needs.  This wage range may also be modified in the future.

This job is also eligible for an annual discretionary bonus.

We offer comprehensive package of benefits including paid time off, medical/dental/vision insurance, 401(k), and any other benefits to eligible employees.

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company's sole discretion, consistent with the law.