Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
OR · On-site
Provide technical leadership and data execution support for strategic external collaborations ... machine learning conferences QUALIFICATIONS: * PhD in Computer Science, Computational Biology ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings ...
We are looking for a Principal Solutions Architect to join our Machine Learning team. In this role ... Translate business and data science requirements into scalable, secure, and resilient architectures ...
... actionable machine learning solutions that drive measurable business outcomes. This role bridges data science, engineering, and operations-owning the full lifecycle from hypothesis and ...
... actionable machine learning solutions that drive measurable business outcomes. This role bridges data science, engineering, and operations-owning the full lifecycle from hypothesis and ...
OR · On-site
The BlueLabs Data Science Team develops deep expertise and uses data to inform strategic advice to ... Expertise building predictive models using regression and machine learning techniques * Ability to ...
OR · On-site
The BlueLabs Data Science Team develops deep expertise and uses data to inform strategic advice to ... Expertise building predictive models using regression and machine learning techniques * Ability to ...
Collaborate with other data scientists, machine learning engineers, data engineers, and business partners * Champion best practices and tooling across a broad data science community * Lead cross ...
Collaborate with other data scientists, machine learning engineers, data engineers, and business partners * Champion best practices and tooling across a broad data science community * Lead cross ...
Use expertise in causal inference, machine learning, complex systems modeling, behavioral decision ... As a Senior Data Scientist, you'll own the analytics and experimentation strategy that powers how ...
Research and implement novel machine learning approaches, including advancing state-of-the-art ... We are hiring a Data Scientist to collaborate directly with clients to design and develop novel ...
Research and implement novel machine learning approaches, including advancing state-of-the-art ... We are hiring a Data Scientist to collaborate directly with clients to design and develop novel ...
$134K - $180K/yr
The Machine Learning Engineer will partner closely with Data Scientists, Applied Scientists, and Software Developers to ensure predictive models make business impact. Job Expectations: * Partner with ...
Machine Learning Tutor
OR · Remote
$18 - $40/hr
... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...
Machine Learning Tutor
OR · Remote
$18 - $40/hr
... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...
Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research and model fine tuning. This role sits at the intersection of research and engineering: the ideal ...
Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research and model fine tuning. This role sits at the intersection of research and engineering: the ideal ...
Machine Learning Tutor
Eugene, OR · Remote
$18 - $40/hr
... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...
Machine Learning Tutor
Eugene, OR · Remote
$18 - $40/hr
... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...
Data Scientist Machine Learning information
See Oregon salary details
$39.6K - $54.9K
2% of jobs
$54.9K - $70.2K
3% of jobs
$70.2K - $85.5K
6% of jobs
$85.5K - $100.8K
9% of jobs
$105.7K is the 25th percentile. Wages below this are outliers.
$100.8K - $116.1K
15% of jobs
The median wage is $126.2K / yr.
$116.1K - $131.3K
22% of jobs
$139.7K is the 75th percentile. Wages above this are outliers.
$131.3K - $146.6K
32% of jobs
$146.6K - $161.9K
3% of jobs
$161.9K - $177.2K
4% of jobs
$177.2K - $192.5K
1% of jobs
$192.5K - $207.8K
2% of jobs
$39.6K
$129.8K
$207.8K
How much do data scientist machine learning jobs pay per year?
What is a Data Scientist Machine Learning job?
A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.
What are the key skills and qualifications needed to thrive in the Data Scientist Machine Learning position, and why are they important?
To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.
Is 40 too late for data science?
Will MLE be replaced by AI?
Which 5 jobs will survive AI?
What are the typical day-to-day responsibilities of a Data Scientist Machine Learning?
On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.
Do data scientists do machine learning?
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U.S. Department Of The Treasury rating
8.2
Based on 13 frontline employees who took The Breakroom Quiz
235th of 692 rated public administrative organizations
Job description
WHAT IS DATA AND ANALYTICS (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions
- Position(s) are to be filled in the following area(s):
- DAO - DATA AND ANALYTICS
- Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
You must meet the following requirements by the cut-off dates as shown in announcement under the 'How to Apply' section.
QUALIFICATION REQUIREMENTS: To qualify for this position, you must meet the qualification requirements outlined below:
BASIC REQUIREMENTS All GRADES: EDUCATION:
You must have a bachelor's or higher degree in mathematics, statistics, computer science, data science or other field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: You may qualify with an equivalent combination of qualifying experience and education with at least 30 semester hours related to Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
EDUCATION/SPECIALIZED EXPERIENCE FOR GS-11: In addition to meeting basic requirements, to be eligible for this position, you must have at least one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal Service. Specialized experience for this position includes: Applying descriptive or inferential statistical methods to analyze data, identify trends or patterns, evaluate results, and develop findings, reports, or recommendations; Using programming, query, or scripting languages, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to extract, transform, analyze, or prepare data for analysis; Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform); Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings; and Creating reports, dashboards, visualizations, written summaries, or presentations to communicate statistical or technical findings to technical or non-technical audiences.
OR
EDUCATION: You may substitute education for specialized experience as follows: A Ph.D. or equivalent doctoral degree as described in the basic requirements in mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
Three (3) full academic years of progressively higher-level graduate education leading to a PH.D or equivalent doctoral degree in mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: You may qualify with an equivalent combination of qualifying experience and education.
SPECIALIZED EXPERIENCE GRADE 12: In addition to the basic requirements above, to be eligible for this position at the GS-12 level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service. Specialized experience for this position includes experience performing all the following:
- Planning and carrying out data analysis assignments by applying descriptive or inferential statistical methods to analyze data from multiple sources, validate results, identify trends or patterns, and develop findings, reports, or recommendations.
- Using programming, query, or scripting languages, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to extract, transform, validate, analyze, visualize, or document structured or unstructured data for data science projects.
- Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
- Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, prescriptive analysis, or exploratory data analysis, to evaluate data, models, programs, or operations and make projections or recommendations.
- Creating and presenting reports, dashboards, visualizations, written summaries, or presentations that explain statistical or technical methods, findings, limitations, or recommendations to managers, stakeholders, customers, or project teams.
SPECIALIZED EXPERIENCE GRADE 13: In addition to the basic requirements above, to be eligible for this position at the GS-13 level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-12 grade level in the Federal service. Specialized experience for this position includes experience performing all the following:
- Independently planning and carrying out data science or statistical analysis projects by defining analytic questions, selecting data sources or methods, analyzing structured or unstructured data, validating results, and developing findings or recommendations.
- Developing or applying statistical, machine learning, operations research, or other data science methods to evaluate programs, operations, compliance, or organizational performance, for example forecasting, predictive or prescriptive modeling, optimization, natural language processing or text analytics, graph or link analysis, or exploratory data analysis.
- Using programming, query, scripting, or analytic tools, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to prepare, transform, document, analyze, and visualize data for data science projects.
- Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
- Documenting analytic approaches, assumptions, limitations, validation results, success measures, or key performance indicators, and presenting technical findings or recommendations to managers, stakeholders, customers, or cross-functional teams.
AND
You must also meet the following requirements:
- MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
- Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
- Completed a formal vocational training program; or
- Received a statement from school authorities agreeing with your preference for employment rather than continuing your education
For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER
What U.S. Department Of The Treasury employees say
Pay
Hours and flexibility
Workplace
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About US Department of the Treasury
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Industry
Public administration
Company size
10,000+ Employees
Headquarters location
Washington, DC, US
Year founded
1789