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Associate Machine Learning Chemistry Jobs in Addison, TX

NTT DATA, Inc.

AI Engineering Associate Director

Plano, TX · On-site

$151.40 - $202.50/hr

AI Engineering Associate Director We are seeking an experienced AI Engineer to design, build, test, and deploy artificial intelligence, machine learning, and generative AI solutions across industries.

Invitation Homes, Inc.

VP, Data Science

Dallas, TX · On-site

Every associate plays a meaningful role in that mission. Invitation Homes does not offer employment ... You will lead a small, high-performing team of data scientists and machine learning engineers ...

Invitationhomes

VP, Data Science

Dallas, TX · Remote

Every associate plays a meaningful role in that mission. Invitation Homes does not offer employment ... You will lead a small, high-performing team of data scientists and machine learning engineers ...

Invitation Homes

VP, Data Science

Dallas, TX · Remote

Every associate plays a meaningful role in that mission. Invitation Homes does not offer employment ... You will lead a small, high-performing team of data scientists and machine learning engineers ...

Invitation Homes LP

VP, Data Science

Dallas, TX · On-site

$178 - $308/hr

Every associate plays a meaningful role in that mission. Invitation Homes does not offer employment ... You will lead a small, high‑performing team of data scientists and machine learning engineers ...

New

Gartner

Associate Data Scientist

Irving, TX · On-site +1

$56K - $57K/yr

Stay current on advancements in machine learning, Generative AI, and agentic systems, bringing new ... That's why we hire associates with the intellectual curiosity, energy and drive to want to make a ...

Gartner

Associate Data Scientist

Irving, TX · On-site

$54K - $55K/yr

Stay current on advancements in machine learning, Generative AI, and agentic systems, bringing new ... That's why we hire associates with the intellectual curiosity, energy and drive to want to make a ...

Carmax

Engineer II, AI/ML

Dallas, TX · On-site

$96K - $132K/yr

Build and maintain production machine learning capabilities spanning featureengineering, training ... Along the way,we help every associate grow their career and achieve their best, at work and in ...

Carmax

Engineer II, AI/ML

Plano, TX · On-site

$88K - $133K/yr

Build and maintain production machine learning capabilities spanning feature engineering, training ... Our amazing team of more than 25,000 associates work together to deliver iconic customer ...

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Showing results 21-40

All JobsAssociate Machine Learning Chemistry JobsAssociate Machine Learning Chemistry Jobs in Addison, TX

Associate Machine Learning Chemistry information

See Addison, TX salary details

$30.5K

$128.8K

$304.5K

How much do associate machine learning chemistry jobs pay per year?

As of Sep 6, 2026, the average yearly pay for associate machine learning chemistry in Addison, TX is $128,811.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,500.00 and $195,500.00 per year, depending on experience, location, and employer.

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 popular job titles related to Associate Machine Learning Chemistry jobs in Addison, TX?

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

What job categories do people searching Associate Machine Learning Chemistry jobs in Addison, TX look for?

The top searched job categories for Associate Machine Learning Chemistry jobs in Addison, TX are:

What cities near Addison, TX are hiring for Associate Machine Learning Chemistry jobs?

Cities near Addison, TX 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 Addison, TX as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, and 4% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $128,811 per year, or $61.9 per hour.

ML / Bioinformatics Data Scientist

IT America Inc

Dallas, TX • Remote

Contractor

Re-posted 7 days ago

Job description

Position: ML / Bioinformatics Data Scientist

Location: Remote (PST work hours)

Duration: Long term contract

About the Role:

We are seeking a highly motivated and collaborative Bioinformatics/ML scientist to join the Computational biology & Medicine department in Computational Sciences COE (Center of Excellence) within Genentech’s Research and Early Development (gRED). The successful candidate will contribute to a cross-functional project that will apply Machine Learning (ML) models to multi-modal datasets collected from clinical trials. This role requires a deep understanding of application of Machine Learning models, a background in biology, a passion for innovation, and a commitment to improving healthcare outcomes through cutting-edge technology.

We are looking for exceptional researchers with a passion for interdisciplinary research and technical problem-solving, and a proven ability to develop and implement research ideas. The candidate is expected to have worked on previous ML modeling projects and applying them to multi-modal datasets to be considered.

About the Project:

The goal of this project is to develop a machine learning model to predict a patient's risk for drug-induced liver toxicity based on a wide variety of patient characteristics including clinical, genetics, omics and safety labs. The focus will be harmonizing these diverse data sources, deriving new features, and  building machine learning models designed to identify a predictive signature that can distinguish between at-risk and not-at-risk patient populations.

Key Responsibilities:

  • Data centralization and harmonization
  • Applying ML methods on assembled dataset to identify patients’ risk for drug-induced liver toxicity.
  • Collaborate with interdisciplinary and cross-functional teams including biologists, chemists, data scientists, and other stakeholders.

Educational Background:

  • PhD degree in quantitative field ( e.g., Computer Science, Computational Biology, Bioinformatics, Statistics, Mathematics) 

Experience:

  • Proven track record of working with statistical modeling techniques, including ML methods, is required
  • Demonstrated interest in problems across biology as applied to the discovery and development of treatments for disease is preferred

Technical Skills:

  • Data Science & Programming: Expertise in Python/R for data manipulation, statistical analysis, and ML model building (required)
  • Multimodal Data & Modeling: Proven ability to work with diverse data types (omics, clinical, imaging) (required).
  • Knowledge of statistics and experience with survival analysis (required)
  • Domain & AI-specific Skills: Experience with NLP/LLMs for feature extraction from unstructured text, and a strong background in a neuroscience (preferred)

Soft Skills:

  • Excellent communication, collaboration, and problem-solving skills (required).

Publications:

  • Strong publication record and experience contributing to research communities.