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Annotation Labelling Jobs in Philadelphia, PA (NOW HIRING)

Responsibilities : • Manage and coach a team of Machine Learning Data Domain analysts to support data annotation and label data/content using annotation tools and analysis • Partner with leads in ...

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate in remote assignments or attend on-site sessions when required * Follow project guidelines and ...

Annotation Labelling information

What is annotation labelling?

Annotation labelling is the process of tagging or marking data—such as images, text, or audio—with relevant information or labels. This is an essential step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms understand and learn from raw data. Annotation labelling can include tasks like identifying objects in photos, transcribing speech, or categorizing text. Skilled annotators ensure accuracy and consistency to improve model performance. People in this role often use specialized tools or software to streamline and standardize the annotation process.

What are the key skills and qualifications needed to thrive as an Annotation Labelling Specialist, and why are they important?

To thrive as an Annotation Labelling Specialist, you need strong attention to detail, data analysis capabilities, and familiarity with data annotation standards, usually supported by a background in computer science or related fields. Proficiency with annotation tools such as Labelbox, CVAT, or Supervisely, and sometimes knowledge of basic programming or scripting, is typically required. Excellent communication, consistency, and the ability to follow complex instructions are crucial soft skills for producing high-quality labeled data. These skills ensure the accuracy and reliability of datasets, which are foundational for successful machine learning and AI model development.

What are some common challenges faced by Annotation Labelling professionals, and how can they be managed?

Annotation Labelling professionals often encounter challenges such as maintaining high accuracy while handling repetitive data, meeting tight deadlines, and adapting to evolving project guidelines. To manage these, it’s important to develop strong attention to detail, regularly communicate with team leads to clarify instructions, and leverage annotation tools efficiently. Collaborating closely with quality assurance teams can also help identify and correct errors early, ensuring consistently high-quality outputs.

What is the difference between Annotation Labelling vs Data Labeling Specialist?

AspectAnnotation LabellingData Labeling Specialist
CredentialsBasic technical skills, attention to detailSimilar skills, sometimes additional domain knowledge
Work EnvironmentData annotation platforms, remote or officeData annotation tasks, often remote or in-office
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, healthcare, retail
Search & ComparisonCommonly compared for entry-level data tasksRelated but broader role

Annotation Labelling involves marking data such as images, text, or videos to train AI models. Data Labeling Specialists perform similar tasks but may have a broader scope, including verifying and managing labeled data. Both roles are essential in AI development, often overlapping in skills and work environment, but Annotation Labelling is more focused on the annotation process itself.

What are popular job titles related to Annotation Labelling jobs in Philadelphia, PA? For Annotation Labelling jobs in Philadelphia, PA, the most frequently searched job titles are:
What job categories do people searching Annotation Labelling jobs in Philadelphia, PA look for? The top searched job categories for Annotation Labelling jobs in Philadelphia, PA are:
What cities near Philadelphia, PA are hiring for Annotation Labelling jobs? Cities near Philadelphia, PA with the most Annotation Labelling job openings:
Data and Analytics - Data Annotation

Data and Analytics - Data Annotation

JP Morgan Chase

Wilmington, DE • On-site

Full-time

Medical, Retirement

This job post has expired today. Applications are no longer accepted.


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 491 frontline employees who took The Breakroom Quiz

58th of 149 rated banks


Job description

Working at Chase means making a real difference every day for your customers, your community and
yourself. How? By putting others first, doing what's right and creating solutions that make lives better.
Build your career on our strong foundation and help shape what's nextfor you and for us. Chase, a
leading provider of diverse financial services worldwide, is actively seeking service-center team
members to create lifelong engaged relationships with our customers by delivering superior service and
quality with every customer interaction

As a Data Domain Architect Analyst within Consumer and Community Banking, you will leverage your business expertise and knowledge of JPMorgan Chase products to collaborate effectively with Data Science, Analytics, and Engineering teams. You will be responsible for developing and enhancing machine learning solutions by gathering, curating, annotating, enriching, and validating data. Additionally, you will create taxonomies and other resources to train machine learning models, extract insights, conduct analysis, and potentially generate content.

Job Responsibilities:

  • Label and annotate call center transcripts and other datasets to support the development of machine learning models.
  • Review and validate the outputs of AI and ML models, ensuring accuracy as well as alignment with business goals and compliance standards.
  • Leverage GenAI tools to conduct deep dives into call datasets to uncover opportunities to improve customer experience.
  • Provide expert guidance to stakeholders on leveraging ML/AI discovery tools for actionable insights. 
  • Draft and refine taxonomies and classification schemas to enhance data organization and model training.
  • Identify and escalate anomalies, errors, or unexpected model behaviors, acting as a critical checkpoint in our AI workflow.
  • Work closely with data scientists, engineers, and business stakeholders to continuously improve annotation processes and model performance.

Required qualifications, capabilities, and skills:

  • Experience with banking products and/or customer service within the financial services industry
  • Bachelor's degree in business or comparable discipline; or equivalent level demonstrated in relevant work experience.
  • Excellent analytical and problem-solving skills and the ability to pay close attention to detail
  • Experience in working with and analyzing large real-world datasets.
  • Ability to interpret and apply business context to technical tasks.
  • Interest in machine learning and willingness to develop new skills in this area.

Preferred qualifications, capabilities, and skills

  • Prior experience with data annotation, conversational analysis, taxonomy development, machine learning projects, and/or quality assurance
  • Familiarity with industry annotation and labeling methods.
  • Working knowledge of information and data retrieval.

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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