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Annotation Finance Jobs in Ohio (NOW HIRING)

Data Engineer

Columbus, OH · On-site

$40 - $55/hr

Support workflows that create models and prepare datasets for annotation and review activities ... layer of financial protection. We offer an ESPP (employee stock purchase program) and a 401K ...

Annotation Finance information

What is an annotation finance job?

An Annotation Finance job typically involves labeling and categorizing financial data to train machine learning models used in fintech applications, such as fraud detection, risk assessment, and financial forecasting. Professionals in this role review and annotate various financial documents, transactions, or datasets to ensure the accuracy and quality of the training data. Attention to detail and a good understanding of financial terminology are important for this position. Annotation Finance specialists may work for financial institutions, technology companies, or data labeling firms. Their contributions are crucial for developing reliable AI systems in the finance sector.

What are common challenges faced by professionals working in annotation finance, and how can they be addressed?

Professionals in Annotation Finance often face challenges related to maintaining high data accuracy and consistency, especially when working with large volumes of financial documents or transactions. Ensuring compliance with evolving regulatory standards and managing sensitive financial information securely are also key concerns. To address these challenges, it's important to stay updated on industry best practices, utilize robust annotation tools, and communicate closely with team members and compliance officers. Regular training and adopting quality assurance protocols can further enhance data reliability and workflow efficiency.

What are the key skills and qualifications needed to thrive as an annotation finance specialist, and why are they important?

To thrive as an Annotation Finance Specialist, you need a solid understanding of financial concepts, data analysis, and attention to detail, typically supported by a degree in finance, accounting, or a related field. Familiarity with data annotation tools, financial modeling software, and spreadsheet applications like Excel is commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret complex data and collaborate with stakeholders. These skills ensure accurate data labeling and analysis, which are critical for driving informed financial decisions and supporting AI or machine learning initiatives in the finance sector.

What is the difference between Annotation Finance vs Data Analyst?

AspectAnnotation Finance
Primary RoleAnnotating financial data for machine learning models in finance
Required SkillsFinancial knowledge, data annotation, attention to detail
Work EnvironmentData labeling teams, finance tech companies
CertificationsBasic financial certifications may help, but not mandatory

Annotation Finance focuses on labeling financial data for AI applications, requiring financial understanding and data annotation skills. Data Analysts analyze and interpret data to inform business decisions, often involving data cleaning and reporting. While both roles work with data, Annotation Finance is specialized in preparing data for machine learning, whereas Data Analysts focus on data analysis and insights.

What job categories do people searching Annotation Finance jobs in Ohio look for?

The top searched job categories for Annotation Finance jobs in Ohio are:

What cities in Ohio are hiring for Annotation Finance jobs?

Cities in Ohio with the most Annotation Finance job openings:

Data Domain Architect Lead

Next Frontier Capital

Columbus, OH • On-site

$130 - $170/hr

Other

Medical, Retirement

Posted 3 days ago

New


Job description

Machine Learning and Artificial Intelligence play a critical role in transforming Consumer and Community Banking Operations. The ability to utilize data in meaningful ways allows us to develop solutions which both our customers and employees can benefit from. Customers expect tailored servicing and Chase is looking to deliver personalization to meet their needs. This is powered by high-quality annotated data and detailed annotation schemes that are the backbone of impactful Artificial Intelligence/Machine Learning ( AI/ML)L algorithms and applications.

As a Data Domain Architect Lead within the Data Annotation team, you will use your domain expertise and people-leading experience to partner your team closely with teams in Data Science, Analytics, and Engineering to develop machine learning solutions. This will involve the collection, curation, annotation, enrichment, and validation of data and the development of taxonomies and other linguistic resources to help train machine learning models, drive insight, analysis, and possible content creation.

Job 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 Data Science, Engineering, and Analytics to develop strategies to optimize training data for machine learning models
  • Lead efforts to identify patterns and trends in conversational data through Natural Language Processing and/or other computational linguistic approaches
  • Collaborate with stakeholders on evaluating the quality of machine learning classification and other output
  • Actively contribute to the team’s continuous learning mindset by bringing in new ideas and perspectives that stretch the thinking of the group
Required qualifications, capabilities, and skills
  • 6+ years of related experience in development of machine learning solutions
  • Familiar with industry annotation and labeling methods
  • Experience with various data modeling techniques and tools
  • Familiar with Finance and Banking products
  • Broad expertise in data technologies; i.e., data warehousing, data processing, data quality concepts, Business Intelligence tools and analytical tools, unstructured data, machine learning
  • Excellent analytical and problem-solving skills and the ability to pay close attention to detail
  • Experience using Python in working with and analyzing large real-world datasets
  • Working knowledge of information and data retrieval
  • Working knowledge of machine learning and artificial intelligence paradigms and libraries
  • Familiar with Large Language Models (LLMs) and prompt engineering
Preferred qualifications, capabilities, and skills
  • Masters or PhD in a related field, or Bachelors
  • Technical understanding of common relational database systems; i.e., Teradata and Oracle
  • Excellent command of the Structured Query Language (SQL)
  • Knowledge of SAS or Scala, and Python languages
  • Knowledge of Advanced Statistics
  • Advanced analytical thinking and problem-solving skills
  • Strong interpersonal & communication skills

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.

AI and ML transform Chase, enabling tailored solutions for customers and employees using quality data and personalization.

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