Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A global technology leader is advancing cutting-edge artificial intelligence and machine learning initiatives through its Data Operations organization. This team collaborates across a broad ecosystem of products and services to deliver high-quality annotated data that supports next-generation AI technologies and innovative customer experiences. The organization is focused on leveraging data science, analytics, and operational excellence to drive business performance and enable the development of transformative AI solutions.
The organization is seeking an experienced Data Science Leader, AIML Data Operations to lead a team of data engineers and data scientists responsible for analytics, experimentation, and operational insights. This role will establish key performance metrics, uncover growth opportunities, and drive data-informed decision-making through scalable research, advanced analytics, and cross-functional collaboration.
The ideal candidate is an experienced people leader with deep expertise in data science and analytics, strong business acumen, and a proven ability to translate complex data into actionable insights. This individual will play a critical role in improving operational performance, enhancing customer experiences, and supporting large-scale AI initiatives.
Key Responsibilities
- Establish a center of excellence for the Data Operations Data Science function by uncovering actionable business insights through collaboration with operational and stakeholder teams.
- Lead large-scale projects from conception through execution, including roadmap development, requirements gathering, risk assessment, contingency planning, and executive communication.
- Define, enhance, and promote key operational metrics that accurately reflect business health and performance.
- Conduct proactive analyses to identify key drivers of operational metrics and recommend optimization strategies.
- Expand self-service reporting capabilities through dashboards, reports, and analytics solutions that empower stakeholders.
- Develop data schemas and instrumentation requirements to enrich operational datasets for new initiatives and projects.
- Identify factors that improve productivity, quality, and operational efficiency.
- Analyze analyst behaviors across platforms to identify opportunities that improve engagement, effectiveness, and overall user experience.
- Build and maintain scalable analytics frameworks that support data-driven decision-making.
- Recruit, develop, mentor, and lead a diverse team of high-performing data engineers and data scientists.
- Foster a culture of innovation, collaboration, and continuous improvement across the analytics organization.
Required Qualifications
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, Economics, or a related field.
- 4+ years of experience managing data science, analytics, or data operations teams.
- 4+ years of hands-on data science experience with a demonstrated ability to translate business goals into meaningful analytical objectives.
- Strong expertise in scalable schema design, relational databases, big data technologies, ETL processes, code management, and query performance optimization.
- Advanced proficiency in SQL-based languages.
- Experience with at least one large-scale data processing language or framework.
- Strong hands-on experience building interpretable machine learning models and advanced analytical solutions using Python, R, or similar tools.
- Proven ability to communicate complex analytical findings to both technical and non-technical audiences.
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, operational, and analytical teams at multiple organizational levels.
- Background managing data science or analytics teams supporting AI/ML annotation and data collection operations.
- Strong passion for artificial intelligence, machine learning, and operational excellence.
- Demonstrated track record of delivering measurable business and operational outcomes through data-driven strategies.
Disclaimer
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