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Remote Data Scientist Machine Learning Jobs (NOW HIRING)

Match Point Solutions

Data Scientist

Pleasanton, CA · Remote

$75 - $80/hr

Remote Rate: $75-$80/hr on W2 Key points: Developing computer vision models that improve ... Applies data science, machine learning and other analytical modeling methods to develop defensible ...

Pluralsight LLC

Data Scientist

$121K - $160K/yr

... machine learning, or a related field, with a proven track record of delivering impactful data science projects. * Strong SQL and Python skills. * This is a remote role; however, applicants located ...

Apogee Global RMS

Senior Data Scientist

San Jose, CA · On-site +1

This person will design, develop, and deploy predictive models, machine learning solutions, and ... Flexible remote work options. * Professional growth in AI/ML and advanced analytics. * Competitive ...

RealPage, Inc.

Data Scientist

Richardson, TX · Remote

$116K - $198K/yr

Responsibilities Machine Learning & Data Science * Develop, evaluate, and deploy predictive and ... Experience building AI solutions that support customer facing products #LI-REMOTE #LI-JL1 Physical ...

Victory

Data Scientist (Remote)

Austin, TX · Remote

About the Data Scientist position We are looking for a skilled Data Scientist who will help us ... Create predictive models and machine-learning algorithms * Modify and combine different models ...

Apogee Global RMS

Senior Data Scientist

San Jose, CA · On-site +1

This person will design, develop, and deploy predictive models, machine learning solutions, and ... Flexible remote work options. * Professional growth in AI/ML and advanced analytics. * Competitive ...

Apogee Global RMS

Senior Data Scientist

San Jose, CA · On-site +1

This person will design, develop, and deploy predictive models, machine learning solutions, and ... Flexible remote work options. * Professional growth in AI/ML and advanced analytics. * Competitive ...

Apogee Global RMS

Senior Data Scientist

San Jose, CA · Remote

This person will design, develop, and deploy predictive models, machine learning solutions, and ... Flexible remote work options. * Professional growth in AI/ML and advanced analytics. * Competitive ...

Extend

Senior Machine Learning Data Scientist

$135K - $165K/yr

As a Senior ML Data Scientist, you will own the development of cutting-edge machine learning models based on signals and transactions from hundreds of millions of users to detect and prevent fraud ...

RealPage, Inc.

Data Scientist

Richardson, TX · Remote

$116K - $198K/yr

Machine Learning & Data Science * Develop, evaluate, and deploy predictive and generative models ... Experience building AI solutions that support customer facing products #LI-REMOTE #LI-JL1 Physical ...

Stellar IT Solutions

Data Scientist

Saint Louis, MO · Remote

Data Scientist Remote 12 Month Contract to hire Data Scientist - Profile Overview This is a data ... Solid traditional Machine Learning: Feature engineering, model training, evaluation * Not a model ...

RealPage, Inc.

Data Scientist

Richardson, TX · Remote

$116K - $198K/yr

Responsibilities Machine Learning & Data Science * Develop, evaluate, and deploy predictive and ... Experience building AI solutions that support customer facing products #LI-REMOTE #LI-JL1 Physical ...

AppOmni

Lead Data Scientist

About the Role AppOmni is looking for a Lead Data Scientist, Risk Intelligence & AI to engineer ... In this role, you will apply statistical modeling, probabilistic reasoning, machine learning, and ...

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All JobsRemote Data Scientist Machine Learning Jobs

Remote Data Scientist Machine Learning information

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$37.5K

$122.7K

$196.5K

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

As of Jun 21, 2026, the average yearly pay for remote 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 Remote Data Scientist specializing in Machine Learning do?

A Remote Data Scientist specializing in Machine Learning uses advanced statistical techniques and programming skills to analyze large datasets and build predictive models, all while working from a remote location. They design, develop, and deploy machine learning algorithms to solve business problems, such as forecasting trends or automating processes. Their work often involves data cleaning, feature engineering, model selection, and collaborating with cross-functional teams to integrate these models into products or services. Remote data scientists typically use tools like Python, R, and cloud-based platforms to perform their tasks efficiently.

What is the difference between Remote Data Scientist Machine Learning vs Remote Data Scientist?

AspectRemote Data Scientist Machine LearningRemote Data Scientist
Required CredentialsMaster's or PhD in Data Science, Computer Science, or related field; experience with ML frameworksSimilar educational background; may focus more on statistical analysis and data visualization
Work EnvironmentPrimarily involves developing ML models, coding in Python/R, and deploying algorithmsFocuses on data analysis, reporting, and insights generation, often with less emphasis on ML deployment
Employer & Industry UsageUsed in tech, finance, healthcare for predictive modeling and automationCommon across various industries for data analysis and business intelligence

While both roles require strong analytical skills and similar educational backgrounds, Remote Data Scientist Machine Learning specializes in developing and deploying machine learning models, whereas Remote Data Scientist focuses more on data analysis and reporting. The ML role often involves coding and algorithm development, making it more technical in nature.

How do remote data scientists specializing in machine learning typically collaborate with cross-functional teams?

Remote data scientists in machine learning often work closely with product managers, engineers, and business analysts through virtual meetings, collaborative platforms, and shared documentation tools. They regularly participate in sprint planning, code reviews, and brainstorming sessions to ensure alignment with project goals. Effective communication and proactive updates are essential for overcoming the challenges of remote collaboration and maintaining project momentum. Building strong relationships with team members across different time zones helps foster innovation and ensures that machine learning solutions are well-integrated into broader business objectives.

What are the key skills and qualifications needed to thrive as a Remote Data Scientist specializing in Machine Learning, and why are they important?

To excel as a Remote Data Scientist in Machine Learning, you need a solid background in statistics, programming (typically Python or R), and a degree in computer science, mathematics, or a related field. Familiarity with tools and frameworks such as TensorFlow, scikit-learn, PyTorch, and experience with cloud platforms like AWS or Azure are often required, along with relevant certifications. Strong problem-solving skills, effective communication, and the ability to work independently are crucial soft skills for remote collaboration and translating insights for diverse stakeholders. These competencies ensure the development of robust models, clear communication of findings, and successful project delivery in a distributed work environment.
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Remote Data Scientist Machine Learning jobs near you
Staff Data Scientist, Machine Learning in Epidemiology and Patient Data Products

Staff Data Scientist, Machine Learning in Epidemiology and Patient Data Products

Valo Health

Lexington, MA • On-site, Remote

Full-time

Medical, Retirement

Posted 5 days ago

Job description

About Us
Valo Health is a human-centric, AI-enabled biotechnology company working to make new drugs for patients faster. The company's Opal Computational Platform transforms drug discovery and development through a unique combination of real-world data, AI, human translational models and predictive chemistry.
Our talented team of biologists, chemists and engineers, armed with advanced AI/ML tools, work together to break down traditional R&D silos and accelerate the speed and scale of drug discovery and development.
Valo is committed to hiring diverse talent, prioritizing growth and development, fostering an inclusive environment, and creating opportunities to bring together a group of different experiences, backgrounds, and voices to work together. We embrace new ways of learning, solve complex problems and welcome diverse perspectives that can help us advance patient-centric innovation.
Valo is headquartered in Lexington, MA, with additional offices in New York, NY and Tel Aviv, Israel. To learn more, visit www.valohealth.com.
About the Role...
As a Staff Data Scientist, Machine Learning in Epidemiology and Patient Data Products, you will be a core member on a team of data scientists building a powerful computational platform for advancing the discovery and development of new medicines. In this role, you will develop machine learning tools for patient data and drive their adoption across teams, under the guidance of epidemiology and biology program leads. Successful candidates will work with a diverse group of scientists and domain experts, in ways that cut across traditional industry boundaries in an innovative startup environment.
What You'll Do...
Your primary areas of responsibility will be:
  • As a senior member of our team, you will lead the development of machine learning (ML) methods and analyses of patient data with diverse stakeholders. For example, integrate clinical insights into supervised and unsupervised learning approaches and generate patient profiles.
  • Perform project-specific hands-on analysis and modeling of high-dimensional longitudinal real-world data, spanning electronic medical records (EHRs), clinical notes, sequencing data, and multi-omics, using modern data science tools in cloud environments.
  • Contribute to the design, implementation, and evaluation of innovative machine learning approaches for patient data to provide novel clinical insights.
  • Be comfortable with scientific uncertainty and embrace curiosity and creative solutions. Many of the challenges we tackle don't have known solutions or established pathways.
  • Use your technical knowledge and intuition to articulate and break down large problems into solvable pieces. There are a lot of problems to solve; you'll need to prioritize which of these are critical-path today from those that can wait.
  • Be a dynamic and active team member, championing shared coding standards, participating in code reviews, and providing regular updates on your work and input into the work of your colleagues.

What You Bring...
  • MS, MPH, or PhD in health data science, biostatistics, or a related quantitative field, with 5 years of experience developing and applying ML methods, including at least 3 years working directly with real-world patient data. Experience in a biopharmaceutical, epidemiological or biostatistical setting is a plus.
  • Extensive experience developing and implementing machine learning solutions in healthcare databases, including EHRs, administrative claims, and patient registries. Familiarity with U.S. and global medical coding ontologies and data models (ICD, ATC, LOINC, SNOMED, CPT, HCPCS, OMOP, etc.). Confident working with highly sparse and high-dimensional data. Experience processing and mining clinical notes is a plus.
  • Extensive experience building, maintaining, and operationalizing ML pipelines, and translating model outputs into meaningful insights for diverse audiences.
  • Broad proficiency across core ML paradigms (e.g., supervised, unsupervised, semi-supervised) and experience with linear and logistic regression, classification and tree-based methods, clustering and dimensionality-reduction techniques, and deep learning architectures. Hands-on experience with representation learning and transformer-based and other sequence models is a plus.
  • Strong grounding in key components of the ML development lifecycle, including evaluation metrics, hyperparameter tuning, model selection, feature engineering and selection, model explainability, and MLOps best practices.
  • Mastery of Python and modern data science tools (e.g., scikit-learn, PyTorch, statsmodels, SciPy, MLlib, MLflow). Experience with AI-assisted coding tools (e.g., Claude Code) is a plus.
  • Comfortable working in ambiguous problem spaces; experience working in a start-up or agile work environment as part of cross-functional project teams.
  • Ability to lead and facilitate meetings and work collaboratively on multi-disciplinary project teams.
  • Exceptional time management, ability to prioritize multiple tasks simultaneously, and deliver products on time every time.
  • Enthusiastic about documentation-ensuring that all analyses are clear and reproducible with thorough documentation of key assumptions and decision points.

You May Also Bring...
  • Advanced knowledge of biostatistics approaches, including inferential and predictive modeling. Experience in causal approaches for observational studies, including propensity score methods, bias adjustment, and covariate selection and adjustment.
  • Familiarity with or exposure to traditional drug discovery and development processes and approaches.

Remote Salary Range
$165,000-$190,000 USD
CA Salary Range
$175,000-$220,000 USD
Compensation for the role will depend on a number of factors, including a candidate's qualifications, skills, competencies, and experience. Valo Health currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Valo Health's good faith estimate as of the date of publication and may be modified in the future.
Please note: At this time, we are only able to consider candidates who currentlyhave permanent US work authorization without the need for immediate or future sponsorship.

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