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Associate Machine Learning Chemistry Jobs in Washington

GRVTY

Data Scientist 2

Annapolis Junction, MD · On-site

... Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related ... physics, chemistry, biology, astronomy), or other science disciplines with a substantial ...

GRVTY

Data Scientist 2

Annapolis, MD · On-site

$115K - $145K/yr

This role combines artificial intelligence and machine learning skills with a strong foundation in ... Bachelor's Degree with 3 years of relevant experience or an Associates degree with 5 years of ...

GRVTY

Data Scientist 2

Annapolis Junction, MD

$115K - $145K/yr

This role combines artificial intelligence and machine learning skills with a strong foundation in ... Bachelor's Degree with 3 years of relevant experience or an Associates degree with 5 years of ...

Cmu

Associate Data Scientist

Arlington, VA

$67K - $68K/yr

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and artificial intelligence to help our government and industry clients research and solve cybersecurity ...

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Associate Machine Learning Chemistry information

What is an associate machine learning chemistry?

Associate Machine Learning Chemists are professionals who combine expertise in chemistry with skills in machine learning to analyze chemical data, develop predictive models, and accelerate scientific discovery. They often work on tasks like predicting molecular properties, optimizing chemical reactions, and supporting drug discovery efforts using computational tools. Typically, these roles require a strong foundation in chemistry, programming experience (often in Python), and familiarity with machine learning libraries. Associate positions are generally entry-level or early-career roles, providing support to senior scientists and data scientists in research and development teams.

How does an associate machine learning chemistry professional typically collaborate with research scientists and engineers?

As an Associate Machine Learning Chemistry professional, you will frequently work alongside research scientists and chemical engineers to develop predictive models and analyze experimental data. Collaboration involves translating chemical problems into machine learning tasks, sharing insights from model results, and participating in interdisciplinary meetings to refine research objectives. Effective communication and teamwork are essential, as you may be required to explain machine learning concepts to non-technical colleagues and integrate their domain expertise into your models. This collaborative environment fosters both scientific discovery and professional growth.

What are the key skills and qualifications needed to thrive as an associate machine learning chemistry, and why are they important?

To thrive as an Associate Machine Learning Chemistry professional, you need a solid background in chemistry, data analysis, and machine learning, typically supported by a relevant degree such as chemistry, computer science, or a related field. Experience with programming languages like Python, machine learning libraries (e.g., TensorFlow, scikit-learn), and cheminformatics software is highly valued. Strong problem-solving skills, attention to detail, and the ability to communicate complex concepts clearly are crucial soft skills. These competencies enable effective collaboration on interdisciplinary teams and the development of innovative solutions in computational chemistry research.

What is the difference between Associate Machine Learning Chemistry vs Associate Data Scientist?

AspectAssociate Machine Learning ChemistryAssociate Data Scientist
Required CredentialsBachelor's or Master's in Chemistry, Data Science, or related fields; familiarity with ML frameworksBachelor's or Master's in Data Science, Statistics, Computer Science; programming skills in Python/R
Work EnvironmentResearch labs, pharmaceutical or chemical companies, biotech firmsTech companies, finance, healthcare, consulting firms
Employer & Industry UsageUsed in industries applying ML to chemical data, drug discovery, materials scienceApplied across industries analyzing large datasets, predictive modeling

Associate Machine Learning Chemistry focuses on applying machine learning techniques specifically to chemical and scientific data, often within research or pharmaceutical settings. In contrast, Associate Data Scientist has a broader scope, working with various data types across multiple industries. Both roles require strong analytical skills and familiarity with ML tools, but their industry focus and data types differ.

What are the most commonly searched types of Machine Learning Chemistry jobs in Washington?

The most popular types of Machine Learning Chemistry jobs in Washington are:

What are popular job titles related to Associate Machine Learning Chemistry jobs in Washington?

For Associate Machine Learning Chemistry jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Associate Machine Learning Chemistry jobs in Washington look for?

The top searched job categories for Associate Machine Learning Chemistry jobs in Washington are:

What cities in Washington are hiring for Associate Machine Learning Chemistry jobs?

Cities in Washington with the most Associate Machine Learning Chemistry job openings:

Associate Machine Learning Chemistry jobs near you
Infographic showing various Associate Machine Learning Chemistry job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 18% Part Time, 2% Temporary, and 5% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution.

Data Scientist III with Security Clearance

Black Eagle Defense

Fort George G Meade, MD • On-site

$128K - $185K/yr

Other

Re-posted 14 days ago

Job description

Job Description SALARY RANGE $128,000 - $185,000/year DUTIES As a successful candidate for the Data Scientist III role, you will devise strategies for extracting meaning and value from large datasets. Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application-specific knowledge. Through analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent in NSA/CSS data holdings. Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others in withdrawing appropriate conclusions from the analysis of such data. Effectively communicate complex technical information to non-technical audiences. Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly shifting NSA/CSS collection, processing, storage, and analytic capabilities and limitations. Required Skills SKILLS Employ some combination (2 or more) of the following skill areas: I. Foundations: (Mathematical, Computational, Statistical) II. Data Processing: (Data management and curation, data description and visualization, workflow and reproducibility) III. Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations) QUALIFICATIONS A Bachelor's Degree with 10 years of relevant experience or an Associate's degree with 12 years of experience may be considered for individuals with in-depth experience that is clearly related to the position. Bachelor's Degree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field (Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g. physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g. algorithms, programming, data structures, data mining, artificial intelligence). College-level requirements, or upper-level math courses designated as elementary or basic do not count. A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university. Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g. Python), statistical analysis (e.g. variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g. data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering. Experience in more than three areas is strongly preferred. Additional Requirements: • Accurately and automatically tokenize language data with spoken or written origins • Develop automated solutions for the annotation of language data with parts of speech information, and improved existing models by scoring performance against human-generated annotations for speech and text • Demonstrated NLP experience

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