Data Scientist - Gen AI / QA

Summary

Join Zyte's Data QA team as a Data Scientist and leverage your AI expertise to ensure the quality and usability of web-scraped data. You will work with large datasets, employing Python and the PyData stack to analyze, manipulate, and visualize data, uncovering quality issues. Collaborate with developers and stakeholders, presenting findings and conclusions effectively. This role requires proficiency in Python, experience with AI-based data quality verification, and strong communication skills. You'll contribute to enhancing data quality for Zyte's enterprise clients, using cutting-edge technologies and working remotely with a global team.

Requirements

• Highly proficient in Python and the PyData stack. Minimum of 3 years (please provide code samples in your application - ideally pertaining to data analysis or Generative AI - via a link to GitHub or other publicly-accessible service)
• BS degree in Computer Science, Engineering, Mathematics, Statistics or equivalent
• Up to speed on the latest advances in Generative AI particularly as they pertain to process automation, web scraping/parsing, and data quality verification
• Comfortable with Prompt Engineering and token/cost optimization
• Familiar with abstraction layers (MCP, Marvin, Langchain etc)
• Experience coding against the APIs of at least one of the Google, OpenAI, or Anthropic models
• Experience in data quality visualization and the visualisation of data quality issues
• Ability to work with very large datasets (into the millions of records)
• Strong knowledge of software QA methodologies, tools, and processes
• Excellent level of written and spoken English; confident communicator; able to communicate on both technical and non-technical levels with various stakeholders on all matters of QA
• Outstanding attention to detail

Responsibilities

• Understand customer web scraping and data requirements; map these requirements to custom AI-based data quality validation techniques, with a focus on achieving pre-established degrees of data quality and uncovering data quality issues
• Draw conclusions about data quality by producing descriptive and evidence-based statistics, summaries, and visualisations
• Supplement existing manual QA and schema validation techniques with AI-based data quality verification
• Collaborate with developers to further troubleshoot and pinpoint solutions
• Present findings and conclusions to stakeholders at various levels (other members of the QA department, developers, project managers, account managers, customers)
• Write high-quality, well-structured code that is maintainable and extensible
• Manage code using GitHub, BitBucket and other version control approaches as applicable

Preferred Qualifications

• Prior experience in a Data QA role (where the focus was on verifying data quality, rather than testing application functionality)
• Familiarity with Jupyter and JupyterLab
• Experience building your own dashboards
• Experience with Spark, BigQuery, and other big data technologies
• Previous remote working experience

Benefits

• Become part of a self-motivated, progressive, multi-cultural team
• Have the freedom and flexibility to work from where you do your best work
• Attend conferences and meet with team members from across the globe
• Work with cutting-edge open source technologies and tools