DescriptionYou 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 multispeaker 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 handson 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 industrystandard 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.
Required Experience:
IC