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Full Time Data Scientist Machine Learning Jobs (NOW HIRING)

Analyze large and complex datasets to identify patterns, build statistical and machine learning ... Integrate the latest data science innovations into product solutions, enhancing data, analytical ...

As an Advance Data Scientist, you will join a high-performing, global team, and be responsible for ... Minimum of 4 years of full time Machine Learning experience applied on top of processes, systems ...

As an Advance Data Scientist, you will join a high-performing, global team, and be responsible for ... Minimum of 4 years of full time Machine Learning experience applied on top of processes, systems ...

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 ...

ISEE is seeking full-time Research Scientists to join our team. The ideal candidate has several ... If you would like more information about how your data is processed, please contact us.

ISEE is seeking full-time Research Scientists to join our team. The ideal candidate has several ... If you would like more information about how your data is processed, please contact us. apply for ...

... Data Analytics and Quality group is seeking an expert in evaluating machine learning and deep ... scientists, and ML Infrastructure engineers to deliver amazing user experiences! Description ...

Docugami is looking for Machine Learning, Data Science and Math PhD researchers to work alongside our world-renowned science and engineering team to create a revolutionary product. We are looking for ...

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and ... Full time/Part time Full time Pay Basis Salary More Information: * Please visit "Why Carnegie ...

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and ... Full time/Part time Full time Pay Basis Salary More Information: * Please visit "Why Carnegie ...

As a Sr Advanced Data Scientist here at Honeywell, you will leverage your expertise in advanced ... Minimum of 4 years of full time Machine Learning experience applied on top of processes, systems ...

As a Sr Advanced Data Scientist here at Honeywell, you will leverage your expertise in advanced ... Minimum of 4 years of full time Machine Learning experience applied on top of processes, systems ...

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Full Time Data Scientist Machine Learning information

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$37.5K

$122.7K

$196.5K

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

As of Aug 21, 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:

Senior Director, Data Science & Machine Learning

Vibrant

Remote

$140K - $180K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 21 days ago


Job description

Department:Technology
Reports to:AVP, Data
Travel: ~10%

Salary Range: $140,000 - $180,000

Vibrant Emotional Health's groundbreaking solutions have delivered high quality services and support, when, where and how people need it for over 50 years. Through our state-of-the-art technology-enabled services, community wellness programs, and advocacy and education work, we are building a society in which emotional wellness can be a reality for everyone.

Position Overview:

The Senior Director, Data Science & Machine Learning provides strategic and technical leadership for Vibrant's Data Science, Machine Learning, and Artificial Intelligence function. Reporting to the Assistant Vice President, Data, this role is responsible for establishing and leading the organization's data science capabilities in support of the 988 Suicide & Crisis Lifeline, H2H (Here 2 Help), Community Programs, and enterprise initiatives. The Senior Director oversees the development of data science strategy, applied research, machine learning engineering standards, and AI governance while ensuring analytical solutions are operationally effective, compliant with applicable regulations, and aligned with organizational priorities. This position serves as the senior technical leader for data science and machine learning, providing direction for team development, cross-functional collaboration, and the responsible implementation of AI-enabled solutions.

Duties/Responsibilities:

  • Define and execute Vibrant's multi-year data science, machine learning, and AI strategy and roadmap in partnership with Technology leadership.
  • Lead and grow the organization's data science and machine learning function, providing mentorship, technical leadership, and career development for team members.
  • Translate organizational priorities into a structured applied research and delivery portfolio with measurable outcomes supporting 988 Lifeline, H2H, Community Programs, and enterprise initiatives.
  • Advise executive leadership on emerging AI technologies, strategic opportunities, and build-versus-buy decisions.
  • Represent Vibrant's data science and AI capabilities with executive stakeholders, federal partners, vendors, and external organizations.
  • Establish and maintain technical standards for machine learning development, validation methodologies, code quality, documentation, reproducibility, and engineering best practices.
  • Coach and mentor data scientists, analysts, and engineers through code reviews, technical guidance, and structured learning opportunities.
  • Recruit, onboard, and retain high-performing data science and AI talent while defining organizational structure and future hiring strategy.
  • Foster a culture grounded in scientific rigor, innovation, responsible AI, collaboration, and continuous improvement.
  • Lead applied research initiatives that translate analytical findings into actionable recommendations and production-ready machine learning solutions.
  • Design and oversee advanced quantitative research, program evaluation, and statistical modeling supporting organizational and federal reporting requirements.
  • Develop and maintain outcome measurement frameworks that evaluate service quality, client outcomes, and operational performance.
  • Oversee development, deployment, and monitoring of NLP and machine learning models supporting crisis services, including call summarization, sentiment analysis, quality assurance, risk detection, and routing optimization.
  • Partner with engineering teams to ensure machine learning models are deployed within secure, HIPAA-compliant infrastructure and monitored throughout the model lifecycle.
  • Ensure all production AI and machine learning systems meet governance, validation, documentation, audit, and regulatory requirements.
  • Serve as the senior technical representative within Data Governance and Responsible AI governance forums, helping establish enterprise AI policies and standards.
  • Collaborate with cross-functional technology, engineering, analytics, governance, and program leaders to ensure machine learning solutions align with operational priorities and clinical appropriateness.
  • Support cooperative agreement deliverables, research reporting, and external program evaluation activities.
  • Other duties as assigned.

Required Skills/Abilities:

  • Executive-level expertise in statistical modeling, machine learning, natural language processing (NLP), and applied artificial intelligence.
  • Deep technical knowledge of end-to-end machine learning lifecycle management, including model development, validation, deployment, monitoring, and optimization.
  • Demonstrated experience leading and scaling high-performing data science, machine learning, or AI teams within complex organizations.
  • Proven ability to establish technical standards, engineering best practices, and scientific rigor across data science initiatives.
  • Strong experience translating applied research into production-ready machine learning systems that deliver measurable organizational impact.
  • Experience designing quantitative research studies, evaluating complex analytical methods, and communicating research findings with appropriate scientific rigor.
  • Knowledge of responsible AI frameworks, model governance, model risk management, fairness evaluation, and explainable AI principles.
  • Experience working with highly regulated or sensitive data environments, including HIPAA, 42 CFR Part 2, or similar regulatory frameworks.
  • Strong ability to partner with executive leadership, engineering, product, analytics, governance, and operational teams to deliver enterprise AI solutions.
  • Demonstrated ability to recruit, mentor, develop, and retain technical talent while fostering a collaborative and psychologically safe team culture.
  • Excellent written and verbal communication skills with the ability to communicate complex technical concepts to technical and non-technical audiences.
  • Strong strategic thinking, decision-making, and organizational leadership capabilities.
  • Demonstrated commitment to responsible AI, ethical machine learning, equity, transparency, and continuous improvement.
  • Experience within healthcare, behavioral health, public health, nonprofit, or other mission-driven organizations strongly preferred.

Required Qualifications:

  • Bachelor's degree in Statistics, Computer Science, Data Science, Epidemiology, Public Health, or a related field required; Master's or Ph.D. strongly preferred.
  • 10+ years of progressive experience in applied data science and/or machine learning engineering.
  • Minimum of 5 years of people leadership experience managing data scientists, machine learning engineers, or research teams.
  • Demonstrated success building, leading, or significantly scaling a data science, machine learning, or artificial intelligence function.
  • Proven experience delivering end-to-end production machine learning solutions, including deployment, monitoring, governance, and continuous model improvement.
  • Strong technical proficiency with Python and modern machine learning frameworks such as scikit-learn, PyTorch, TensorFlow, Hugging Face, MLflow, Snowflake, dbt, or comparable technologies.
  • Experience working in healthcare, behavioral health, crisis services, public health, or other federally regulated environments strongly preferred.
  • Familiarity with HIPAA, 42 CFR Part 2, and governance requirements related to sensitive data.
  • Experience with causal inference methodologies, advanced statistical analysis, or program evaluation preferred.
  • Experience supporting federal grants, cooperative agreements, or government-funded programs is highly desirable.

Physical Requirements:

  • Must be able to remain in a stationary position 50% of the time.
  • Will constantly operate a computer and other standard office equipment.
  • May occasionally ascend and descend a ladder to service office equipment or facilities.
  • Will frequently communicate over video calls with internal and external stakeholders to provide updates, technical guidance, and project status.

We determine base pay through a comprehensive review of skills, experience, education, certifications, geographic location, and other relevant factors. The range listed reflects the compensation parameters for the role and does not represent the full compensation package. A complete overview of compensation and benefits will be provided by the Talent Acquisition team during the hiring process.

Full time employees will be eligible for excellent comprehensive benefits, including medical, dental, vision, supplemental income insurance, employer paid disability insurance, employer paid life insurance, pre-tax FSA for medical and dependent care, and 401K available.

Studies have shown that women and people of color are less likely to apply for jobs unless they believe they are able to perform every task in the job description. We are most interested in finding the best candidate for the job, and that candidate may be one who comes from a less traditional background. Vibrant will consider any equivalent combination of knowledge, skills, education and experience to meet minimum qualifications. If you are interested in applying, we encourage you to think broadly about your background and skill set for the role.

Vibrant Emotional Health is an equal opportunity employer. Applicants are considered for positions without regard to veteran status, uniformed service member status, race, creed, color, religion, gender, gender identity, sex, sexual orientation, citizenship status, national origin, marital status, age, physical or mental disability, genetic information, caregiver status or any other category protected by applicable federal, state or local laws.

Please be aware that fictitious job openings, consulting engagements, solicitations, or employment offers may be circulated on the Internet in an attempt to obtain privileged information, or to induce you to pay a fee for services related to recruitment or training. Vibrant does NOT charge any application, processing, or training fee at any stage of the recruitment or hiring process. All genuine job openings will be posted on our careers page and all communications from the Vibrant recruiting team and/or hiring managers will be from an @vibrant.org email address.