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Machine Learning Data Associate Jobs in Mansfield, MA

Lead Machine Learning Engineer

Cambridge, MA · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Construct optimized data pipelines to feed ML models * Leverage continuous integration and ...

Principal Machine Learning Scientist The Principal Machine Learning Scientist will develop novel ... Focuses on simulating human learning activities, improving system performance through data analysis ...

Lead Machine Learning Engineer

Cambridge, MA · On-site

$112K - $147K/yr

We build data-driven tools that use machine learning to prevent risks & automatically detect issues ... our associates work and provide value to our customers. * Design, develop, test, deploy, and ...

Lead Machine Learning Engineer

Cambridge, MA · On-site

$112K - $147K/yr

We build data-driven tools that use machine learning to prevent risks & automatically detect issues ... our associates work and provide value to our customers. * Design, develop, test, deploy, and ...

Machine Learning Intern

Boston, MA · On-site

$27 - $42/hr

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Lead Machine Learning Engineer (IC)

Cambridge, MA · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be ... Construct optimized data pipelines to feed ML models * Leverage continuous integration and ...

Showing results 41-60

Machine Learning Data Associate information

See Mansfield, MA salary details

$10

$19

$32

How much do machine learning data associate jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for machine learning data associate in Mansfield, MA is $19.84, according to ZipRecruiter salary data. Most workers in this role earn between $16.30 and $21.11 per hour, depending on experience, location, and employer.

What is a machine learning data associate?

Machine Learning Data Associates are professionals who support the development of machine learning models by preparing, labeling, and validating data sets. Their work ensures that data used for training algorithms is accurate, consistent, and properly annotated. They may also assist with data cleaning, quality checks, and sometimes basic data analysis tasks. This role is crucial in industries where high-quality labeled data is essential for building effective AI systems.

What are the key skills and qualifications needed to thrive as a machine learning data associate?

To thrive as a Machine Learning Data Associate, you need strong analytical skills, attention to detail, and a basic understanding of data annotation and labeling processes, often supported by a degree in computer science or a related field. Familiarity with data management tools, annotation platforms, and sometimes scripting languages like Python is typically required. Strong communication, collaboration, and problem-solving abilities help you work efficiently with data science teams and ensure high-quality outcomes. These skills and qualities are crucial for producing accurate datasets that directly impact the effectiveness of machine learning models.

How does a machine learning data associate typically collaborate with data scientists and engineers within a project team?

As a Machine Learning Data Associate, you play a vital role in supporting data scientists and engineers by annotating, cleaning, and organizing large datasets to ensure high data quality. You'll frequently communicate with team members to clarify labeling guidelines, provide feedback on data inconsistencies, and report any edge cases encountered during annotation. This collaboration ensures that the datasets used for training machine learning models are accurate and comprehensive, directly impacting the success of the project. Expect regular team meetings and ongoing feedback loops to maintain alignment with evolving project requirements.

What is the difference between Machine Learning Data Associate vs Data Analyst?

AspectMachine Learning Data AssociateData Analyst
Required SkillsData cleaning, labeling, basic programming, understanding of ML workflowsData interpretation, visualization, statistical analysis
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing, healthcare sectors
Common CertificationsData Science certifications, Python, SQLExcel, Tableau, SQL certifications

The main difference is that Machine Learning Data Associates focus on preparing and labeling data specifically for machine learning models, while Data Analysts interpret data to generate insights for business decisions. Both roles require strong data skills and often overlap, but their primary objectives and work environments differ.

How do I become a machine learning data associate?

To become a machine learning data associate, candidates typically need a high school diploma or equivalent, with some roles preferring a bachelor's degree in computer science, data science, or related fields. Relevant skills include data annotation, understanding of machine learning concepts, and proficiency with tools like Excel, SQL, or data labeling platforms. Gaining experience through internships or certifications can improve job prospects in this field.

Is a Machine Learning Data Associate a good job?

A Machine Learning Data Associate role involves preparing and managing data for machine learning models, often requiring skills in data cleaning, annotation, and familiarity with tools like Python or SQL. It can be a good entry-level position for those interested in AI and data science, offering opportunities to develop technical skills and gain industry experience. Compensation and job satisfaction vary depending on the employer and location, but it generally provides a solid foundation for a career in machine learning or data analysis.

What cities near Mansfield, MA are hiring for Machine Learning Data Associate jobs?

Cities near Mansfield, MA with the most Machine Learning Data Associate job openings:

Infographic showing various Machine Learning Data Associate job openings in Mansfield, MA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $41,258 per year, or $19.8 per hour.

(Senior) Scientist, Machine Learning

Flagship Pioneering, Inc.

Cambridge, MA • On-site

$100K - $136K/yr

Full-time

Medical, Retirement

Re-posted 4 days ago


Job description

What if... you could join an organization that creates, resources, and builds life sciences companies that invent breakthrough technologies in order to transform health care and sustainability?

COMPANY DESCRIPTION

Expedition Medicines is a privately held, early-stage biotechnology company pioneering the emerging field of Protein Editing. At Expedition Medicines we create small molecules that edit protein structure and function to unlock presently undruggable targets and a broad array of therapeutic modalities. Our platform integrates novel small molecule chemistry and chemoproteomic discovery technologies with Machine Learning (ML) to enable generative design. Expedition Medicines is backed by Flagship Pioneering, bringing their courage, vision, and resources to guide Expedition Medicines from platform validation to patient impact. We are seeking collaborative, relentless problem solvers that share our passion for impact to join us!

THE ROLE

Expedition is seeking a motivated and innovative (Senior) Scientist, Machine Learning to join our team. In this role, you will play a critical role in developing, evaluating, and applying machine learning approaches that connect Expedition's proprietary chemoproteomics data with quantum chemistry, electronic structure, and generative molecular design. The successful candidate will combine strong expertise in modern machine learning with a deep understanding of molecular representation, quantum chemistry, and computational drug discovery to drive impact across Expedition's drug discovery programs.

This individual will contribute to the advancement of a state-of-the-art AI platform for covalent drug discovery, with a focus on linking large-scale atom-precision experimental data to physically meaningful features such as electronic structure, reactivity, and DFT-derived descriptors. A key part of the role will be applying generative models directly to active drug discovery programs in close partnership with medicinal chemistry, while developing rigorous benchmarks to evaluate model performance and guide platform improvement. The ideal candidate is highly collaborative, scientifically rigorous, comfortable with hands-on data curation, and capable of independently driving projects in a fast-paced research environment.

KEY RESPONSIBILITIES

  • Develop, implement, and evaluate innovative machine learning methods for connecting (macro-)molecular quantum chemical features, reactivity modeling, covalent bond formation, and proteome-wide target engagement data
  • Design and implement rigorous benchmarks to evaluate model performance, including retrospective, prospective, and program-relevant validation strategies
  • Refine, fine-tune and apply Expedition's foundational models to our drug discovery programs in close partnership with medicinal chemistry teams, supporting compound design, prioritization, and iterative learning from experimental results
  • Perform hands-on data curation, quality control, and dataset construction to ensure that models are trained and evaluated on high-quality, biologically and chemically meaningful data
  • Develop scalable featurization and modeling pipelines for large molecular datasets, including quantum chemistry outputs, conformer ensembles, protein-ligand interaction data, covalent reactivity data, and experimental chemoproteomics data
  • Collaborate closely with computational, chemistry, biology, and proteomics teams to translate platform data into actionable models for discovery programs
  • Partner with engineering teams to productionize modeling workflows, improve data infrastructure, and build self-serve capabilities for chemistry and discovery teams
  • Communicate technical findings, model performance, and scientific implications clearly across cross-functional teams

PROFESSIONAL EXPERIENCE & QUALIFICATIONS

  • Ph.D. in machine learning, computational chemistry, chemical physics, computer science, applied mathematics, or a related discipline with 2+ years of industry experience, or M.S. degree with 6+ years of industry experience
  • Experience with quantum chemistry, DFT, electronic structure methods, or post-DFT descriptors.
  • Experience building molecular ML models including graph neural networks, geometric deep learning, equivariant architectures, diffusion models, or related approaches. Publications or preprints in, e.g., NeurIPS, ICML, ICLR, bioRxiv a strong plus.
  • Experience applying generative models, molecular design models, or active learning workflows to drug discovery or chemistry optimization problems
  • Experience working closely with medicinal chemistry teams to prioritize compounds, interpret model outputs, and incorporate experimental feedback into model development
  • Experience developing rigorous model evaluation frameworks, benchmarks, and validation strategies for molecular ML or scientific machine learning applications and an ability to curate, clean, integrate, and analyze complex, large-scale scientific datasets from multiple sources
  • Proficiency with Python and modern ML frameworks such as PyTorch, PyTorch Geometric, DGL, or related tools and cheminformatics and molecular modeling toolkits such as RDKit, ORCA, Gaussian, Q-Chem, or related software is preferred
  • Experience with scalable data processing, model training, and analysis workflows for large scientific datasets
  • Experience with covalent chemistry, reaction modeling, structure-based design, or chemoproteomics data is a plus
  • Ability to work closely with experimental scientists and translate biological and chemical questions into computational strategies
  • Excellent communication and cross-functional collaboration skills

LOCATION:Cambridge, MA

ABOUT FLAGSHIP PIONEERING

Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity's most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  

Flagship has been recognized twice on FORTUNE's "Change the World" list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company's annual list of the World's Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.

At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact.

We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship.

Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, "FSP") do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.

#LI-MB1

The salary range for this role is $180,000 - $258,500. Compensation for the role will depend on a number of factors, including a candidate's qualifications, skills, competencies, and experience. Expedition Medicines currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Expedition Medicines's good faith estimate as of the date of publication and may be modified in the future.