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Temporary Data Scientist Machine Learning Jobs in New York

Carlyle

AlpInvest Embedded Data Scientist

New York, NY · On-site

$190K - $220K/yr

The ideal candidate can move seamlessly between developing machine learning models and engaging ... AI & Data Science Innovation * Develop and improve predictive models leveraging structured and ...

6AM City, LLC

Data Scientist

Manhattan, NY · On-site

$85 - $90/hr

Are you a data scientist who enjoys working directly with clients and making a direct and ... This position requires a strong command of statistical techniques and machine learning algorithms ...

Carlyle

AlpInvest Embedded Data Scientist

New York, NY · On-site

$190K - $220K/yr

The ideal candidate can move seamlessly between developing machine learning models and engaging ... AI & Data Science Innovation * Develop and improve predictive models leveraging structured and ...

Atrosphere Technologies

Data Scientist

Manhattan, NY · On-site

$80 - $120/hr

Join our data science team to help transform data into actionable insights. You will work on ... Develop and implement machine learning models * Create data visualizations and reports

Cadent

Lead Data Scientist

New York, NY · On-site

M.S. or higher in computer science, mathematics, operations research, statistics or related discipline with a focus on machine learning; or the equivalent of 6-7 years' experience in a Data Science ...

Compunnel

PHD AI/ML Data Scientist

New York, NY · On-site

... Machine Learning, advanced data modeling, and statistical analysis. The ideal candidate will have extensive experience designing, developing, validating, and deploying scalable AI/ML solutions to ...

Smarsh

Lead Data Scientist

Manhattan, NY · On-site

$166 - $214/hr

Summary As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh , you will spearhead the ... Development of machine learning models and other analytics following established workflows, while ...

Fusemachines

Lead Data Scientist- IBM Watson

New York, NY · On-site

$100K - $150K/yr

The role requires extensive experience in data analysis, agentic AI, statistical modeling, machine learning, and data visualization, as well as the ability to lead a team of data scientists and ...

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Temporary Data Scientist Machine Learning information

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.

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

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

What are popular job titles related to Temporary Data Scientist Machine Learning jobs in New York?

For Temporary Data Scientist Machine Learning jobs in New York, the most frequently searched job titles are:

What job categories do people searching Temporary Data Scientist Machine Learning jobs in New York look for?

The top searched job categories for Temporary Data Scientist Machine Learning jobs in New York are:

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

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

Temporary Data Scientist Machine Learning jobs near you
Infographic showing various Temporary Data Scientist Machine Learning job openings in New York as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

AlpInvest Embedded Data Scientist

Carlyle

New York, NY • On-site

$190K - $220K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 25 days ago

Job description

Position Summary:

Join our dynamic Investment Data Science Team as an Embedded Data Scientist to partner directly with investment professionals across Primaries, Secondaries, and CoInvestments.

This role sits at the intersection of investing, data science, artificial intelligence, and product development. The successful candidate will work alongside deal teams to develop analytical frameworks, generate proprietary investment insights, and build scalable products that enhance investment decision-making.

Unlike traditional data science roles, this position requires the ability to operate as both a technical expert and a strategic thought partner. The ideal candidate can move seamlessly between developing machine learning models and engaging with investment professionals on questions related to manager selection, fund evaluation, portfolio construction, investment pricing, and market intelligence.

This individual will help advance several strategic initiatives, including GP Scoring, OneDay Pricing, AI-powered diligence workflows, portfolio intelligence, and market signal generation.

Primary Responsibilities

Investment Analytics & Decision Support

  • Partner directly with investment professionals across Primaries, Secondaries, and Co-Investments to support live investment opportunities.
  • Translate investment questions into analytical frameworks, models, and actionable insights.
  • Conduct quantitative analyses to evaluate fund managers, investment strategies, portfolio performance, and market opportunities.
  • Present findings and recommendations to investment teams and senior leadership.

Product & Model Development

  • Develop and enhance proprietary GP Scoring methodologies used to evaluate private equity managers.
  • Build scalable analytical products that integrate into AlpInvest's investment workflows.
  • Design and deploy machine learning, statistical, and AI-driven solutions to improve investment decision-making.
  • Contribute to the development of One-Day Pricing capabilities for LP interest transactions.
  • Support the creation of market intelligence, portfolio monitoring, and company intelligence products.

AI & Data Science Innovation

  • Develop and improve predictive models leveraging structured and unstructured investment datasets.
  • Apply modern AI techniques, including LLMs, agent-based workflows, and retrieval systems, to investment research and diligence processes.
  • Collaborate with engineering and product teams to productionize analytical capabilities.
  • Identify opportunities to automate workflows and improve scalability across investment processes.

Stakeholder Engagement

  • Build strong relationships with investment professionals and become a trusted advisor across business lines.
  • Gather requirements, prioritize opportunities, and translate business needs into technical solutions.
  • Communicate complex analytical concepts to both technical and non-technical audiences.
  • Help drive adoption of data science products and insights throughout the organization.

Requirements

Education & Certificates

  • Bachelor's degree or higher (MS, PhD, MBA, or equivalent), required
  • Concentrations in Data Science, Computer Science, Statistics, Mathematics, Economics, Engineering, Finance, or a related quantitative discipline, preferred.

Professional Experience

  • 8+ years of overall relevant technical experience, required
  • Experience in Data Science, Machine Learning, Quantitative Analytics, Applied AI, or related fields, with a proved track record of success.
  • Experience building and deploying production-grade analytical products and models.
  • Demonstrated ability to work directly with senior business stakeholders and solve complex business problems.
  • Experience operating in highly ambiguous environments and managing multiple priorities simultaneously.
  • Strong programming skills in Python and experience with modern data science libraries and frameworks.
  • Deep understanding of statistical modeling, machine learning, experimentation, and predictive analytics.
  • Experience working with structured and unstructured datasets at scale.
  • Familiarity with cloud-based analytics environments and modern data platforms.
  • Experience applying generative AI, LLMs, or agent-based systems is strongly preferred.
  • Experience within private equity, asset management, investment management, alternative investments, financial services, or investment technology.
  • Familiarity with investment performance metrics, portfolio analytics, fund structures, or manager evaluation frameworks.
  • Experience developing products that combine quantitative analysis with business decision-making.

Benefits/Compensation

The compensation range for this role is specific to New York and takes into account a wide range of factors including but not limited to the skill sets required/preferred; prior experience and training; licenses and/or certifications.

The anticipated base salary range for this role is $190,000 to $220,000.

In addition to the base salary, the hired professional will enjoy a comprehensive benefits package spanning retirement benefits, health insurance, life insurance and disability, paid time off, paid holidays, family planning benefits and various wellness programs. Additionally, the hired professional may also be eligible to participate in an annual discretionary incentive program, the award of which will be dependent on various factors, including, without limitation, individual and organizational performance.

Due to the high volume of candidates, please be advised that only candidates selected to interview will be contacted by The Carlyle Group.


About Us:


The Carlyle Group (NASDAQ: CG) is a global investment firm with $475 billion of assets under management, across 678 investment vehicles as of March 31, 2026. Founded in 1987 in Washington, DC, Carlyle has grown into one of the world's largest and most successful investment firms, with more than 2,500 professionals operating in 28 offices in North America, Europe, the Middle East, Asia and Australia.

Carlyle's purpose is to connect people, ideas, and capital to fuel growth for companies and performance for investors, which range from public and private pension funds to wealthy individuals and families to sovereign wealth funds, unions and corporations. Carlyle invests across three segments - Global Private Equity, Global Credit and Carlyle AlpInvest - and has deep expertise across industries, markets, and geographies.

At Carlyle, we believe that a wide spectrum of experiences and viewpoints drives performance and success. Our CEO, Harvey Schwartz, has stated that, "To build better businesses and create value for all of our stakeholders, we are focused on assembling leadership teams with the strongest insights from a range of perspectives." Reflecting this view, emphasis is placed on development, retention and inclusion through our internal processes and seven Employee Resource Groups (ERGs). We cultivate a culture where ideas are openly shared and challenged, connecting diverse expertise and perspectives to drive enduring value.


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