Data Analyst - Quality & Annotation Expert- Associate

You are a strategic thinker passionate about driving solutions in Data Annotation and Validation. You have found the right team.

As a Data Analyst within our Asset Management Data Science team, you will be responsible for setting and improving our organizational objectives, and ensuring their consistent accomplishment.

Job Responsibilities:

• Work on data labeling tools and annotate data for machine learning models. Sift through structured and unstructured data; identify the right content and annotate with the right label.
• Develop comprehensive test plans and strategies for data science projects, including data validation, model testing, and performance evaluation.
• Collaborate with stakeholders, including data scientists, data engineers, and product managers.
• Conduct thorough data validation and verification processes to ensure data accuracy and consistency.
• Design and execute test cases for models, ensuring they meet performance and accuracy standards.
• Validate model outputs and conduct regression testing to ensure consistent results.
• Utilize tools like Snorkel, Datasaur, and Apptek for model performance monitoring, data labeling, and speech annotation.
• Develop and maintain automated testing scripts and tools to streamline the QA process.
• Implement continuous integration and continuous deployment (CI/CD) practices for data science projects.
• Transcribe verbatim audio recordings, single and multi-speaker of varying dialects and accents, and identify relevant keywords and sentiment labels.
• Build a thorough understanding of data annotation and labeling conventions and develop documentation/guidelines for stakeholders and business partners

Required qualifications, capabilities, and skills:

• At least 5 years of hands-on experience in data collection, analysis, or research.
• Proven experience in data quality assurance, data management, or a similar role.
• Experience in Python programming.
• Proficiency in data querying and validation using SQL, with experience in Snowflake .
• Experience in constructing dashboards to effectively visualize and communicate data insights.
• Experience with data annotation, labeling, entity disambiguation, and data enrichment.
• Familiarity with industry-standard annotation and labeling methods and tools like Label Studio, Snorkel, Datasaur, and Apptek.
• Familiarity with Machine learning and AI paradigms such as text classification, entity recognition, information retrieval.
• Creative and disruptive, loves embracing the challenge of rigorous testing to uncover vulnerabilities and enhance system robustness.
• Understanding of data governance principles and practices.

Preferred qualifications, capabilities, and skills:

• Strong financial knowledge is preferred.
• Familiarity with Machine learning and AI paradigms such as text classification, entity recognition, information retrieval.
• Strong financial knowledge is preferred.