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Full Time 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 ...

Move fast, learn fast: hundreds of experiments run monthly; rigorous experimentation culture Why this Role is Different Most Data Science roles currently on the market are focused on optimizing ad ...

Infosys/Apple is seeking a highly skilled and motivated Data Scientist / Machine Learning Engineer to join their team. The role involves developing and implementing advanced analytics and machine ...

Data Scientist

Boston, MA

$160K - $180K/yr

Role Description This is a full-time Data Scientist role with Newton Research, Inc., working from ... Strong foundation in data analysis, statistical modeling, and machine learning concepts.

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Full Time Data Scientist Machine Learning information

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

As of Sep 11, 2026, the average yearly pay for full time 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 full time data scientist specializing in machine learning do?

A Full Time Data Scientist specializing in Machine Learning is responsible for analyzing large datasets to discover patterns and insights, and for building, testing, and deploying machine learning models to solve business problems. They use statistical techniques, programming skills, and domain knowledge to turn raw data into actionable information. Their day-to-day tasks often include data cleaning, feature engineering, model selection, and performance evaluation. They also collaborate with other teams to integrate machine learning solutions into products or decision-making processes. This role typically requires proficiency in languages like Python or R, and familiarity with tools such as TensorFlow, scikit-learn, or PyTorch.

What are the key skills and qualifications needed to thrive as a full time data scientist specializing in machine learning?

To thrive as a Full Time Data Scientist Machine Learning, you need strong analytical skills, expertise in statistics, machine learning techniques, and a relevant degree in computer science, mathematics, or a related field. Proficiency with programming languages such as Python or R, experience with machine learning libraries like TensorFlow or scikit-learn, and familiarity with data visualization and big data platforms are typically required. Critical thinking, problem-solving abilities, and effective communication are essential soft skills for collaborating with stakeholders and translating data insights into business value. These skills are crucial for developing robust models, interpreting complex data, and driving impactful, data-driven decisions within organizations.

What are some common challenges faced by full time data scientists specializing in machine learning, and how can they be addressed?

Full-time Data Scientists in Machine Learning often encounter challenges such as dealing with messy or incomplete data, tuning complex models for optimal performance, and effectively communicating technical insights to non-technical stakeholders. Addressing these challenges usually involves collaborating closely with data engineers to improve data quality, staying updated with the latest ML techniques, and developing strong communication skills to translate findings into actionable business strategies. Additionally, regular code reviews and participation in cross-functional meetings help ensure alignment and foster a supportive team environment.

What is the difference between Full Time Data Scientist Machine Learning vs Data Analyst?

AspectFull Time Data Scientist Machine LearningData Analyst
Required CredentialsBachelor's/Master's in Data Science, Computer Science, or related; knowledge of ML algorithmsBachelor's in Statistics, Mathematics, or related; proficiency in data visualization and SQL
Work EnvironmentDeveloping ML models, programming in Python/R, deploying algorithmsData cleaning, reporting, creating dashboards, analyzing datasets
Industry UsageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Full Time Data Scientist Machine Learning roles focus on building and deploying machine learning models, requiring advanced programming and statistical skills. Data Analysts primarily interpret data, generate reports, and support decision-making with less emphasis on ML techniques. Both roles are vital but differ in technical depth and responsibilities.

What cities are hiring for Full Time Data Scientist Machine Learning jobs?

Cities with the most Full Time 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 Full Time Data Scientist Machine Learning jobs?

States with the most job openings for Full Time Data Scientist Machine Learning jobs include:

What are popular job titles related to Full Time Data Scientist Machine Learning jobs?

For Full Time Data Scientist Machine Learning jobs, the most frequently searched job titles are:

What other helpful pages are available for Full Time Data Scientist Machine Learning?

Other pages related to Full Time Data Scientist Machine Learning:

Data Scientist - Machine Learning Practitioner

Ann Arbor, MI • On-site, Remote

BlueConduit
Internet and IT • 11 - 50 employees

$140K - $150K/yr

Full-time

Medical, Dental, Vision, Retirement

This job post has expired today. Applications are no longer accepted.


Job description

Company overview

BlueConduit is an infrastructure analytics SaaS company and social enterprise helping communities make better, faster, and more equitable decisions about critical water infrastructure. Our founding team pioneered predictive modeling for lead service line replacement in Flint, Michigan, and BlueConduit now works with hundreds of cities and utilities across North America.

Our platform helps utilities, municipalities, government agencies, and consultants combine fragmented infrastructure records, field observations, geospatial data, and predictive models to identify risk, prioritize work, meet compliance requirements, and communicate clearly with the public. We are a remote-first team committed to using data science for social good and building tools that are trusted by the people making high-stakes infrastructure decisions.

The role

BlueConduit is hiring a Data Scientist to improve and expand the machine learning models at the core of our infrastructure analytics platform. In this role, you will work on models that help cities prioritize infrastructure investments, reduce risk, and improve drinking water outcomes. You will strengthen our existing modeling workflows, help launch new model products and asset classes, and communicate results clearly to both technical and nontechnical audiences.

This is a strong fit for someone who combines rigorous applied ML judgment with product-minded execution: you enjoy messy real-world data, care about model validation and uncertainty, can build repeatable workflows rather than one-off analyses, and like explaining technical work to people who need to act on it.

In this role you will be expected to be using the latest available AI tools to code productively. You will need to understand what you're building and coding, and understand agentic AI workflows that involve best practices, including unit tests, built-in code reviews, and extensive documentation in your commits for fellow data scientists and software engineers.

This role reports to the VP of Data Science.

What you'll do
  • Build, validate, and improve machine learning and statistical models used in BlueConduit's infrastructure analytics products
  • Help design, build, and launch new model products and model classes that broaden the assets and risks BlueConduit can predict
  • Improve data science workflows, model evaluation, reproducibility, and handoffs into software/product systems
  • Work with heterogeneous municipal, infrastructure, geospatial, and field-observation datasets to generate actionable risk predictions
  • Design validation approaches and communicate model uncertainty, limitations, and tradeoffs clearly to internal teams and customers
  • Use modern AI coding tools such as Claude Code, Codex, or similar systems to accelerate development while applying strong independent programming judgment
  • Use multiple AI agents to contribute to extremely robust workflows and code pipelines with built-in testing and reviews
  • Support customer-facing analysis and present findings in ways that are clear, accurate, and useful for nontechnical decision-makers
  • Contribute to R&D that scales the impact, reliability, and reach of BlueConduit's predictive methods

BlueConduit is a small, remote, and growing team, so this is an opportunity to shape both the role and the next generation of our data science products.

What we're looking for
  • Strong Python-based data science experience, including pandas, NumPy, scikit-learn, and production-quality analysis workflows
  • An undergraduate degree in a quantitative field (e.g., CS, math, stats, physics)
  • Experience building, validating, and improving machine learning or statistical models on messy real-world data
  • Experience building repeatable data science workflows in a product at a SaaS company or similarly operational environment
  • Ability to communicate modeling results, uncertainty, and tradeoffs clearly to technical and nontechnical stakeholders
  • Fluency using modern AI coding tools - including coordinating work of AI agents - to accelerate development, grounded in strong independent programming ability and judgment
  • Strong data visualization, verbal communication, and written communication skills
  • Comfort with Git-based development workflows
  • Attention to detail, curiosity, and commitment to building models that are understandable, usable, and trusted by the people making infrastructure decisions
  • Passion for socially impactful data science, environmental justice, and public-interest technology
We're especially interested in candidates with one or more of the following
  • A rigorous graduate degree in a quantitative field, or equivalent applied experience
  • Experience modeling asset classes beyond BlueConduit's current water distribution portfolio, such as fire risk, wastewater, hydraulic systems, climate risk, insurance risk, or other infrastructure domains
  • Experience with geospatial data, GIS systems, GeoPandas, or spatial modeling
  • Experience creating a new model product or extending an existing model product to a new domain or asset class
  • Experience with both global/cross-location models and local/site-specific models
  • Experience with methodologies beyond classical ML, such as neural networks, transformers, transfer learning, or other modern ML approaches
  • Experience with cloud-based model workflows, model tracking, versioning, Databricks, PySpark, or distributed computing
  • Familiarity with infrastructure, water quality, government data, or regulated public-sector decision environments
  • Experience working in Agile product development environments
  • Aptitude and interest in building with rapid iteration cycles involving prototyping, receiving feedback, and rebuilding
Location

Remote

Compensation
  • Expected salary range: $140,000-$150,000, commensurate with experience
  • Equity options
  • Health, vision and dental benefits
  • Simple IRA benefit with company contribution matching

Every qualified applicant will receive consideration for employment without regard to race, age, color, religion, sex, sexual orientation, or national origin.

Employment Type: FULL_TIME