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Senior Data Scientist Machine Learning Jobs (NOW HIRING)

This is an exciting Senior Data Scientist/Machine Learning opportunity to have a real impact and be a large fish in a small pond! As a Senior Data Scientist at, you will: * Develop natural language ...

The Data Scientist, Machine Learning will support Basketball Operations by developing and deploying machine learning models to inform decision making across player evaluation, game strategy, and ...

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As a Data Scientist Machine Learning, you will work within a small data science team focusing on predictive modeling, natural language processing, computer vision, recommender systems, and OCR ...

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Senior Data Scientist Machine Learning information

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$41.5K

$142.5K

$201K

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

As of May 30, 2026, the average yearly pay for senior data scientist machine learning in the United States is $142,460.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $166,500.00 per year, depending on experience, location, and employer.

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

To thrive as a Senior Data Scientist in Machine Learning, you need advanced expertise in statistics, programming (Python or R), and machine learning algorithms, typically backed by a relevant degree (such as in computer science or mathematics) and several years of experience. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and cloud platforms (AWS, GCP, or Azure), as well as experience with big data technologies, is essential. Strong problem-solving, communication, and project leadership skills help drive impactful solutions and foster collaboration across teams. These skills ensure the successful design, deployment, and scaling of machine learning models that deliver business value.

How does a Senior Data Scientist specializing in Machine Learning typically collaborate with cross-functional teams?

Senior Data Scientists in Machine Learning often work closely with product managers, software engineers, and business analysts to understand project goals and translate them into actionable data solutions. They are responsible for communicating complex technical concepts to non-technical stakeholders, ensuring that ML models align with business objectives. Collaboration frequently involves participating in regular strategy meetings, reviewing data pipelines with engineering teams, and providing insights that guide product development. This cross-disciplinary teamwork is essential for successfully deploying machine learning models into production environments.

What does a Senior Data Scientist specializing in Machine Learning do?

A Senior Data Scientist in Machine Learning leads the development, implementation, and optimization of advanced statistical and machine learning models to solve business problems. They analyze large, complex datasets, design predictive algorithms, and collaborate with cross-functional teams to integrate models into production systems. Additionally, they mentor junior data scientists, contribute to setting technical strategy, and often communicate findings to stakeholders to drive data-driven decision-making.

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

AspectSenior Data Scientist Machine LearningData Scientist
Required CredentialsMaster's or PhD in CS, Statistics, or related field; experience with ML frameworksBachelor's or Master's in relevant field; foundational knowledge of data analysis
Work EnvironmentAdvanced analytics teams, R&D, product developmentData analysis teams, business intelligence, reporting
Employer & Industry UsageTech companies, finance, healthcare, e-commerceSimilar industries, often entry to mid-level roles

The main difference is that Senior Data Scientist Machine Learning roles require more experience, advanced skills in ML frameworks, and often involve leading projects. Data Scientists typically focus on data analysis and reporting with less emphasis on complex ML models. Senior roles also tend to involve mentorship and strategic input.

More about Senior Data Scientist Machine Learning jobs
What cities are hiring for Senior Data Scientist Machine Learning jobs? Cities with the most Senior 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 Senior Data Scientist Machine Learning jobs? States with the most job openings for Senior Data Scientist Machine Learning jobs include:
Infographic showing various Senior Data Scientist Machine Learning job openings in the United States as of May 2026, with employment types broken down into 85% Full Time, 14% Part Time, and 1% Contract. Highlights an 53% Physical, 8% Hybrid, and 39% Remote job distribution, with an average salary of $142,460 per year, or $68.5 per hour.
Senior Data Scientist

Other

Posted 2 days ago


Job description

We're an exciting seed round, Boston-based,contract management and analysis tool for technology companies to track and search key liabilities across all contracts and make finding key contract data for audits and other diligence easier. This is an exciting Senior Data Scientist/Machine Learning opportunity to have a real impact and be a large fish in a small pond!
As a Senior Data Scientist at, you will:
  • Develop natural language processing systems that help our customers understand their contracts
  • Work with a wide range of structured and unstructured data sources
  • Design and build customized, large-scale cloud-based machine learning systems
We're looking for people to:
  • Examine data from multiple sources and communicate insights to stakeholders
  • Design natural language processing solutions including named-entity recognition and text classification
  • Lead a team of data analysts
  • Work with our product managers and machine learning engineers during development phase.
Nice-to-haves include:
  • Familiarity with Python NLP frameworks and libraries such as scikit, NumPy, and XGBoost
  • Experience working with engineers on algorithm development, architecture planning, and development
  • Knowledge of Github and software development best practices