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.