Data Annotator

Posted 13 Days Ago
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London, Greater London, England
1-3 Years Experience
Information Technology
The Role
The Data Annotator will accurately extract, label, and annotate data from various financial documents. Responsibilities include ensuring the quality of automated data extraction, correcting OCR errors, and collaborating with teams to optimize processes. This role plays a key part in enhancing operational workflows and supports machine learning model training.
Summary Generated by Built In

Stenn is one of the leading FinTechs in Europe and a category leader in the verticals and markets it operates in. Founded in 2015, Stenn’s purpose is to connect international SMEs to the global financial system, helping to bridge a reported $3.6 trillion (USD) financing gap through a fast, simple online platform. To date, Stenn has enabled over $18 billion (USD) of finance to SMEs in 3 verticals and 4 markets, with capital provided by several blue-chip banks and institutional fund managers across the globe. 

Rapid expansion continues at Stenn, as under-served SMEs seek financing solutions to manage significant macroeconomic and supply chain disruption; and this follows our $50 million Series A fundraise in 2022, valuing Stenn at $900 million.

Our HQ is in London with employees across the globe, including the USA, Europe and China. We are made up of diverse, highly skilled professionals who work in an innovative way to develop and drive our business further. Our people are empowered to work autonomously through a trusting leadership style which encourages learning.

The Role

To support our continued growth, we are seeking a Data Annotator to join our Operations team. This role is essential in ensuring the accurate extraction of data from trade and financial records, as well as other relevant documents. You will be responsible for data labelling, quality control, and annotation, in addition to helping train machine learning models used in automating our internal processes.

The role will require working extensively with Optical Character Recognition (OCR) tools, reviewing and correcting the extracted data, and ensuring that the information meets our accuracy standards. This position will directly contribute to reducing operational bottlenecks by improving the accuracy and automation of OCR technologies, allowing us to scale document-related processes and minimise manual interventions.


Responsibilities


Data Labelling and Annotation:

    • Annotate and label data fields in various types of digital documents, including invoices, transportation records, financial statements, corporate filings, and contracts.
    • Review the accuracy of automated data extraction and undergo routine quality assurance checks to ensure consistency in labelled data.
    • Manually correct OCR output errors to ensure smooth operational workflows.
    • Identify patterns of systematic errors and report them to relevant teams for resolution.
    • Manage high volumes of document annotations while maintaining exceptional accuracy.

OCR System Operations:

    • Learn and proficiently operate OCR tools used in the data annotation process.
    • Collaborate closely with cross-functional teams to provide ongoing feedback on the OCR tool's performance.
    • Identify patterns and issues with submitted documents and OCR outputs, recommending optimisations for current processes.
    • Work with external teams to provide feedback and assist in the successful training of AI modules related to document recognition.


Operational Requirements:

    • Maintain and update internal knowledge bases and documentation, organising records of labelled data logs.
    • Collaborate with the operations team to streamline workflows, improve productivity, and reduce manual interventions.
    • Ensure compliance with internal policies, particularly around data security and privacy protocols, when handling sensitive information.


A little bit about you:


Experience:

    • 1-2 years of experience in data annotation, document analysis, or other data-centric roles.
    • Experience with OCR and annotation tools is preferred.
    • Familiarity with large datasets and document processing, especially in a financial context, is advantageous.

Technical Knowledge:

    • Basic understanding of machine learning models, particularly in relation to character recognition and natural language processing (NLP).
    • Experience in analysing and correcting OCR outputs is a plus.

Attention to Detail:

    • High attention to detail and precision, with the ability to process tasks under pressure and meet tight deadlines.

Problem-Solving:

    • Strong analytical and problem-solving skills, particularly when identifying recurring errors or operational inefficiencies.

Communication:

    • Excellent communication skills to collaborate effectively across teams and provide feedback on system improvements.

We appreciate the support recruitment agencies can provide, however our in-house team do not require any 3rd party assistance at this time. 

At Stenn, we believe that every team member deserves to feel like they belong. We foster a culture of inclusivity, respect, and collaboration where everyone's unique perspectives are valued. Join us and be part of a team where you can thrive and grow, both professionally and personally.


The Company
HQ: London
249 Employees
Hybrid Workplace
Year Founded: 2015

What We Do

A leading digital marketplace enabling growth for businesses engaged in international trade, e-commerce and digital services.

Please visit us at https://stenn.com/ to learn more.

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