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Senior Data Scientist Machine Learning Jobs (NOW HIRING)

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 ...

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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 ...

Key Responsibilities The Senior Data Scientist applies strong expertise in machine learning, data science, and other artificial intelligence techniques to design, prototype and build next generation ...

The Senior Data Scientist provides advanced analytics, machine learning, and investigative data support. Working closely with criminal investigators, auditors, and technical stakeholders, this ...

Senior Data Scientist (Machine Learning & MLOps) Our client is seeking a Data Scientist (Machine Learning & MLOps) to help build the next generation of its intelligent water utility platform. This is ...

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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 Aug 9, 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.

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

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.

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.

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 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 August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $142,460 per year, or $68.5 per hour.

Senior Data Scientist / Machine Learning Engineer

Waypoint Human Capital

Mclean, VA • On-site

Full-time

Posted 9 days ago


Job description

Position Title: Senior Data Scientist / Machine Learning Engineer
Position Type: Full-Time, On-Site
Position Location: Tysons, VA
Clearance Required: Active TS/SCI with CI Polygraph or Full Scope Polygraph
Waypoint's client is seeking a dynamic Senior Data Scientist / Machine Learning Engineer with an active TS/SCI CI Poly or higher to join their team. The Senior Data Scientist / Machine Learning Engineer will work directly with data scientists, software engineers, and subject matter experts in the definition of new analytics capabilities able to provide federal customers with the information they need to make proper decisions and enable their digital transformation.
This position works directly with data scientists, software engineers, and subject matter experts to research, design, and deploy machine learning algorithms that support federal customers in digital transformation and data-driven decision making. They will contribute to new analytics capabilities and assist customers in building their own applications. This position requires a bachelor's degree in Computer Science, Electrical Engineering, Statistics, or a related field, 5 to 10 years of relevant experience, and strong Python and applied ML skills. An active TS/SCI with CI Polygraph or Full Scope Polygraph is required.
Responsibilities
The responsibilities include, but are not limited to:
  • Research, design, implement, and deploy Machine Learning algorithms for enterprise applications.
  • Assist and enable federal customers to build their own applications.
  • Contribute to the design and implementation of new features.

Required
  • Active Top Secret clearance with CI Polygraph or Full Scope Polygraph.
  • Bachelor's degree in Computer Science, Electrical Engineering, Statistics, or equivalent fields required.
  • MS or PhD in Computer Science, Electrical Engineering, Statistics, or equivalent fields preferred.
  • Minimum 5–10 years relevant work experience preferred.
  • Excellent programming skills in Python.
  • Applied Machine Learning experience (regression and classification, supervised, and unsupervised learning).
  • Strong mathematical background (linear algebra, calculus, probability, and statistics).
  • Experience with scalable Machine Learning (MapReduce, streaming).
  • Ability to drive a project and work both independently and in a team.
  • Smart, motivated, can-do attitude, and seeks to make a difference.
  • Excellent verbal and written communication skills.
  • Passion for developing team-oriented solutions to complex engineering problems.
  • Thrive in an autonomous, empowering, and exciting environment.
  • Ability to collaborate across multiple functional teams to improve scalability.
  • Ability to convey highly technical concepts and information in written form to both technical and non-technical audiences.
  • Ability to work on multiple concurrent projects.
  • Strong self-motivation and the ability to work with minimal supervision.
  • Team-oriented, energetic, results- and delivery-focused, with a strong commitment to quality and meeting deadlines.
  • Ability to work in an Agile environment.

Desired
  • Hands-on experience deploying and operating applications using IaaS and PaaS on major cloud providers, including Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP).
  • Proficient in leveraging modern LLM tools to accelerate development workflows and enhance code quality.
  • Experience with deep learning.
  • Experience with natural language processing (NLP).
  • Experience with computer vision.
  • Experience with reinforcement learning.