Data Scientist, AIML

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Company Overview

A global technology leader is focused on developing innovative products, services, and AI-powered experiences that impact millions of users worldwide. Its AI and Machine Learning Data Operations organization collaborates across multiple business functions to deliver high-quality annotated data that supports cutting-edge AI technologies and future product development. The Capacity Planning & Analytics team plays a critical role by providing forecasting, optimization, experimentation, reporting, and advanced analytics to improve operational efficiency and data quality at scale.

The organization is seeking a highly motivated Data Scientist, AIML to lead analysis of annotation project trends and uncover insights related to annotator performance, task complexity, and data characteristics. This role will help optimize task design, project structures, workflows, and capacity planning through data-driven decision-making and rigorous analytical methods.

The ideal candidate will be an experienced data scientist with expertise in analytics, experimentation, forecasting, and machine learning. Success in this role requires strong cross-functional collaboration skills and the ability to transform complex data into actionable recommendations that improve operational performance and customer outcomes on a global scale.

Key Responsibilities

• Analyze trends across annotation projects to identify patterns in annotator performance, task complexity, and data characteristics.
• Develop insights that improve project scoping, task design, guideline development, and workflow optimization.
• Evaluate tasks and data types that can benefit from automation and collaborate with stakeholders to improve efficiency.
• Translate behavioral insights and empirical findings into optimized project structures before project launch.
• Partner with cross-functional teams to design, execute, and analyze A/B experiments while establishing best practices.
• Support capacity forecasting and optimization through quantitative analysis and scenario modeling.
• Identify key drivers that improve productivity, operational efficiency, and quality outcomes.
• Contribute to a holistic understanding of analyst behavior across platforms and identify opportunities for improved user experience and operational synergies.
• Surface and communicate critical data insights that support strategic business decisions.

Required Qualifications

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, Economics, or a related field.
• 4+ years of experience in data science with demonstrated ability to translate business goals into meaningful analytical objectives.
• Experience with scalable data architecture, relational databases, big data technologies, ETL processes, code management, and query optimization.
• Advanced proficiency in SQL and at least one large-scale data processing or programming language.
• Strong hands-on experience developing interpretable machine learning models and advanced analytical solutions using Python, R, or similar tools.
• Excellent analytical, problem-solving, and data storytelling skills.
• Ability to collaborate effectively with both technical and non-technical stakeholders.

Preferred Qualifications

• Master’s degree or PhD in Computer Science, Statistics, Mathematics, Engineering, Economics, or a related field.
• Experience deploying Large Language Models (LLMs) and Generative AI solutions to improve operational efficiency.
• Excellent communication and presentation skills with strong attention to detail.
• Experience collaborating across business, operations, analytics, and engineering teams.
• Passion for Artificial Intelligence, Machine Learning, and Operations with a demonstrated record of delivering measurable business impact.

Disclaimer

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