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Machine Learning Data Associate Jobs in Nahant, MA

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Showing results 21-40

Machine Learning Data Associate information

See Nahant, MA salary details

$9

$18

$30

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

As of Sep 14, 2026, the average hourly pay for machine learning data associate in Nahant, MA is $18.40, according to ZipRecruiter salary data. Most workers in this role earn between $15.10 and $19.57 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 Nahant, MA are hiring for Machine Learning Data Associate jobs?

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

Infographic showing various Machine Learning Data Associate job openings in Nahant, MA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, and 5% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $38,263 per year, or $18.4 per hour.

Senior Machine Learning Engineer - Hybrid

Boston, MA • On-site

$175K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago


Key responsibilities

  • Design, recommend, and implement platforms and infrastructure using MLOps/LLMOps best practices.

  • Collaborate with data scientists and data engineers to design and implement scalable and efficient machine learning pipelines.

  • Deploy machine learning models into production and monitor their performance.


Job description

Employer: John Hancock Life Insurance Company (USA) Job Site: 200 Berkeley Street, Boston, MA 02116 Job Title: Senior Machine Learning Engineer Job Duties

Package models, automate workflows, and operationalize analytics solutions to generate business value for organization’s insurance division as member of U.S. based Advanced Analytics Team. Duties include:

  • Design, recommend, and implement platforms and infrastructure using MLOps/LLMOps best practices;
  • Collaborate with data scientists and data engineers to design and implement scalable and efficient machine learning pipelines;
  • Evaluate and optimize machine learning models for performance and scalability;
  • Deploy machine learning models into production and monitor performance;
  • Manage data science infrastructure to streamline model development and deployment;
  • Support development and deployment of high-quality Generative AI technologies including prompt engineering and RAG applications, and fine-tuning LLM models using Azure AI Studio;
  • Propose appropriate tools including languages, libraries, and frameworks for implementing projects;
  • Work closely with infrastructure architects to design scalable and efficient solutions;
  • Collaborate with cross-functional teams to integrate machine learning models into existing systems and processes;
  • Keep abreast of latest advancements in machine learning, MLOps, and LLMOps techniques, and contribute to continuously improving organization’s machine learning capabilities; and
  • Mentor associates and peers on MLOps best practices.

Work Arrangement requirement: Hybrid from Boston office (3 days from office, 2 days from home)

Minimum Requirements

Master’s degree or foreign equivalent in Data Science, Computer Science, Computer Engineering, or related field and 3 years of machine learning experience.

Experience must include the following, which may be gained concurrently:

Minimum Requirements

Master’s degree or foreign equivalent in Data Science, Computer Science, Computer Engineering, or related field and 3 years of machine learning experience.

Experience must include the following, which may be gained concurrently:

Minimum Requirements

Master’s degree or foreign equivalent in Data Science, Computer Science, Computer Engineering, or related field and 3 years of machine learning experience.

Experience must include the following, which may be gained concurrently:

  • 3 years of experience developing and deploying machine learning models for model training, optimization, evaluation, and production deployment through APIs, microservices, or cloud-based serving infrastructure using Python, TensorFlow, PyTorch, Scikit-learn, Keras, or XGBoost.
  • 3 years of experience deploying and managing infrastructure using Linux OS, containerization technologies (Docker, Kubernetes), relational databases (PostgreSQL, MySQL, and Oracle) and NoSQL databases (MongoDB, Cassandra, Elasticsearch and Redis) using AWS, Azure or GCP cloud platforms.
  • 3 years of experience designing and building scalable ETL pipelines and feature engineering workflows for large-scale datasets using distributed processing frameworks including Apache Spark (PySpark, Spark SQL), Hadoop ecosystem tools, or cloud-based big data services including Databricks and EMR.
  • 2 years of experience developing and deploying Large Language Models including BERT, GPT-series, T5, or LLaMA, or other transformer-based NLP models using cloud-based platforms and open-source frameworks.
  • 3 years of experience designing hybrid machine learning systems combining rule-based decision engines with ML models for fraud detection, compliance, claims adjudication, or automated decision-making in regulated environments.
  • 3 years of experience applying machine learning algorithms, statistical modeling, and data analysis techniques for model optimization, generating actionable insights, and working with structured and unstructured data to solve business problems in financial services, fintech, insurance, or other regulated industries.
  • 3 years of experience with Agile development methodologies including Scrum, Kanban, or SAFe for sprint planning, iterative development cycles, and cross-functional team collaboration in enterprise environments.
  • 2 years of experience developing and deploying computer vision models for document processing, OCR, information extraction, or image classification using OpenCV, Tesseract, or cloud-based vision APIs.

Salary: $175,000 per year

The role being advertised is an existing vacancy.

マニュライフとジョン・ハンコックについて

マニュライフ・ファイナンシャル・コーポレーションは、「あなたの未来に、わかりやすさを」を提供する、国際的な大手金融サービスプロバイダーです。当社について詳しくは、https://www.manulife.co.jp/ lをご覧ください。

マニュライフは機会均等を是とする雇用主です

マニュライフ/ジョン・ハンコックでは、多様性を受け入れます。私たちは、サービス提供先であるお客さまと同様に、多様な人材を引きつけ、育成し、定着させ、文化や個人の力を受け入れる包括的な職場環境を促進するよう努めています。当社は公正な採用、定着、昇進、報酬に努めています。当社のすべての慣行およびプログラムは、人種、祖先、出身地、肌の色、民族的出自、市民権、宗教または宗教的信念、信条、性別(妊娠および妊娠関連の状態を含む)、性的指向、遺伝的特徴、退役軍人としての地位、性自認、性に関する表明、年齢、婚姻状況、家族状況、障害、または適用法で保護されるその他の要因に対する一切の差別を行うことなく管理されます。

雇用への平等なアクセスを提供するために、障壁を取り除くことが当社の優先事項です。人事担当者は、応募者が応募プロセス中に合理的配慮を要求する場合に協力します。配慮要求のプロセス中に共有されるすべての情報は、適用される法律およびマニュライフ/ジョン・ハンコックのポリシーに準拠した方法で保存および使用されます。申請プロセスにおいて合理的配慮を要求するには、hr@manulife.comまでご連絡をお願いします。

Referenced Salary Location

Boston, Massachusetts

Working Arrangement

ハイブリッド勤務

Salary range is expected to be between

$107,450.00 USD - $199,550.00 USD

Employees also have the opportunity to participate in incentive programs and earn incentive compensation tied to business and individual performance. The actual salary will vary depending on local market conditions, geography and relevant job-related factors such as knowledge, skills, qualifications, experience, and education/training. If you are applying for this role outside of the primary location, please contact hr@manulife.com for the salary range for your location.

Manulife/John Hancock offers eligible employees a wide array of customizable benefits, including health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage, adoption/surrogacy and wellness benefits, and employee/family assistance plans. We also offer eligible employees various retirement savings plans (including pension/401(k) savings plans and a global share ownership plan with employer matching contributions) and financial education and counseling resources. Our generous paid time off program in the U.S. includes up to 11 paid holidays, 3 personal days, 150 hours of vacation, and 40 hours of sick time (or more where required by law) each year, and we offer the full range of statutory leaves of absence.

We use data and analytics technologies, such as artificial intelligence (AI), and automated processing tools, to analyze and process the information you provide to us or third parties in the application process. For more information, please refer to our personal information collection statement.

Know Your Rights I Family & Medical Leave I Employee Polygraph Protection I Right to Work I E-Verify

Company: John Hancock Life Insurance Company (U.S.A.)

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