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Remote Data Scientist 2025 Grad Jobs (NOW HIRING)

Data Scientist | Remote Looking for a Senior Data Scientist & Machine Learning Engineer to bridge the gap between advanced AI engineering and strategic business insights. Need to take ownership of ...

TS/SCI with Poly Potential for Remote Work: ORA_ON_SITE Description The Data Scientist will apply their technical and analytical capabilities to support key business and security objectives. This ...

Data Scientist Job Location: REMOTE Pay: $85/hr on W2 Duration: 12 months Long-term role with opportunities for hire CPG analytics background preferred. Digital Commerce Marketing Analytics ...

Data Scientist

Hartford, CT · On-site +1

$90K - $135K/yr

Data Scientist - GD08AE We're determined to make a difference and are proud to be an insurance ... This role can have a Hybrid or Remote work arrangement depending on experience and skillset.

Data Scientist

Charlotte, NC · On-site +1

$90K - $135K/yr

Data Scientist - GD08AE We're determined to make a difference and are proud to be an insurance ... This role can have a Hybrid or Remote work arrangement depending on experience and skillset.

The Data Scientist supports data integration and modeling for a portfolio of customers, supporting ... We are fully remote, with team members in the United States and Europe. Benefits include: * Equity ...

Data Scientist

$74K - $111K/yr

The Data Scientist is responsible for developing and applying statistical, machine learning, and ... We recognize the benefits of flexible, remote working arrangements for eligible roles and are ...

Data Scientist

OR · On-site +1

$74K - $111K/yr

The Data Scientist is responsible for developing and applying statistical, machine learning, and ... We recognize the benefits of flexible, remote working arrangements for eligible roles and are ...

Data Scientist

$121K - $160K/yr

As a Data Scientist, you will play a pivotal role in our Data Science and Machine Learning (DSML ... This is a remote role; however, applicants located within 45 miles of our Westlake/Dallas, TX ...

Data Scientist

Chicago, IL · On-site +1

$90K - $135K/yr

Data Scientist - GD08AE We're determined to make a difference and are proud to be an insurance ... This role can have a Hybrid or Remote work arrangement depending on experience and skillset.

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Data Scientist

Durham, NC · Remote

$51 - $58/hr

... Data Scientist to support environmental health and extreme weather research initiatives ... This is a long-term contract opportunity offering remote work flexibility. We are looking for ...

They are seeking a Data Scientist to join their Data Science & Insight team, focusing on developing AI and machine learning solutions to enhance efficiency and decision-making within the finance ...

New

They are seeking a Data Scientist II / III to join their Data Science & Insight team, focusing on developing AI and machine learning solutions to enhance decision-making in finance. The role involves ...

New

Data Scientist Salary - Market (DOE) REMOTE / Work From Home Full-Time / Direct-Hire As Data Scientist, you will spearhead the end-to-end development of sales forecasting and demand sensing models ...

New Demand - Data Scientist Remote * Total Years of experience 10-12 years * 6 months+ * Occasional travel to the client location is required. * Candidates might need to overlap with offshore on need ...

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Remote Data Scientist 2025 Grad information

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$37.5K

$122.7K

$196.5K

How much do remote data scientist 2025 grad jobs pay per year?

As of Jun 10, 2026, the average yearly pay for remote data scientist 2025 grad 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 is the difference between Remote Data Scientist 2025 Grad vs Remote Data Analyst 2025 Grad?

AspectRemote Data Scientist 2025 GradRemote Data Analyst 2025 Grad
Required CredentialsBachelor's in Data Science, Computer Science, or related field; some roles prefer internships or projectsBachelor's in Statistics, Data Analysis, or related field; internships beneficial
Work EnvironmentCollaborative teams, research-focused, often in tech or finance industriesBusiness intelligence teams, reporting, and data visualization tasks
Employer & Industry UsageTech companies, finance, healthcare, and consulting firmsRetail, marketing, finance, and healthcare sectors

The main difference is that Remote Data Scientist 2025 Grad roles focus on building models and advanced analytics, while Remote Data Analyst 2025 Grad positions emphasize data interpretation, reporting, and visualization. Both roles require strong analytical skills and relevant degrees, but Data Scientists typically work on more complex algorithms and predictive modeling.

What are the key skills and qualifications needed to thrive as a Remote Data Scientist (2025 Grad), and why are they important?

To thrive as a Remote Data Scientist (2025 Grad), a solid foundation in statistics, machine learning, and programming (Python or R), along with a relevant degree in data science, computer science, or a related field, is essential. Familiarity with data analysis tools like SQL, cloud platforms such as AWS or GCP, and experience with visualization libraries and machine learning frameworks are typically required. Strong problem-solving skills, effective communication, and the ability to collaborate remotely set standout candidates apart. These competencies enable data-driven decision-making, effective teamwork, and successful project delivery in a distributed work environment.

What are some common challenges faced by Remote Data Scientists who are recent graduates, and how can they be addressed?

Remote Data Scientists who are recent graduates often encounter challenges such as effective communication with distributed teams, managing time zones, and navigating the company's data infrastructure without in-person guidance. Proactively scheduling regular check-ins with mentors or team members, utilizing collaborative tools like Slack and JupyterHub, and participating in virtual team meetings can help address these obstacles. Additionally, seeking out online communities and training resources can aid in continuous learning and professional growth while working remotely.

What are Remote Data Scientist 2025 Grad roles?

Remote Data Scientist 2025 Grad roles are entry-level positions targeted at recent or soon-to-be graduates with a background in data science, statistics, computer science, or related fields. These jobs allow individuals to work from anywhere while analyzing data, building predictive models, and generating insights to help organizations make informed decisions. Candidates typically collaborate with teams virtually, utilize programming languages like Python or R, and leverage tools such as SQL and machine learning frameworks. These roles often require strong analytical skills, proficiency in data visualization, and the ability to communicate findings to both technical and non-technical stakeholders.
More about Remote Data Scientist 2025 Grad jobs
What cities are hiring for Remote Data Scientist 2025 Grad jobs? Cities with the most Remote Data Scientist 2025 Grad job openings:
What are the most commonly searched types of Data Scientist 2025 Grad jobs? The most popular types of Data Scientist 2025 Grad jobs are:
What states have the most Remote Data Scientist 2025 Grad jobs? States with the most job openings for Remote Data Scientist 2025 Grad jobs include:
Infographic showing various Remote Data Scientist 2025 Grad job openings in the United States as of June 2026, with employment types broken down into 15% As Needed, 39% Full Time, 15% Part Time, and 31% Contract. Highlights an 98% Physical, and 2% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Data Scientist

Contractor

Posted 3 days ago


Job description

Data Scientist | Remote
Looking for a Senior Data Scientist & Machine Learning Engineer to bridge the gap between advanced AI engineering and strategic business insights. Need to take ownership of the entire ML lifecycle-from critical data analysis to architecting production-grade, GCP-based ML pipelines and advanced analytics systems. Translate ambiguous business problems into scalable, production-grade AI solutions, drive technical excellence, and mentor team members in engineering best practices.
Roles & Responsibilities
  • Technical Ownership & MLOps: End-to-end responsibility for designing, deploying, and monitoring scalable ML pipelines and AI solutions. You design from scratch, or convert experimental notebooks, into robust, production-ready code with automated CI/CD and feature management.
  • Critical Analysis & Strategy: Autonomously dive into complex datasets to uncover growth opportunities, validate model assumptions, and deliver executive-level insights on business metrics, forecasting, and user behavior.
  • Data Engineering & Collaboration: Act as a bridge to Data Engineering teams to co-design robust data architecture. You possess strong foundational skills in building optimized data pipelines, modeling clean schemas, and ensuring high-quality data ingestion for downstream ML models.
  • Senior Leadership: Act as a strategic partner to product and business stakeholders, manage project delivery timelines, and champion rigorous code quality and best practices across the team.
  • Preferred Domain Expertise: Strong preferred experience in Marketing Science, specifically around building and calibrating Marketing Mix Models (MMMs) and attribution frameworks to optimize ROI and budget allocation.

Tools and Technologies
  • Google Cloud Platform (GCP)
    • Data & Analytics: BigQuery (Advanced SQL, BigQuery ML), Cloud Storage
    • AI & MLOps: Vertex AI (Pipelines, Model Registry, Feature Store), Agent Builders / Agent Platforms, Kubeflow
  • Languages & Core Data Science
    • Programming: Python (Expert), SQL (Advanced)
    • Libraries: Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch
  • Preferred Marketing Science & Bayesian Modeling
    • MMM Frameworks: Meridian, LightweightMMM
    • Probabilistic Programming: PyMC, Stan, or similar Bayesian libraries
  • Engineering & CI/CD
    • DevOps: Git, Docker, CI/CD pipelines, Airflow