Principle Data Scientist

Maximize Your Impact with TP

Welcome to TP, a global hub of innovation and empowerment, where we redefine the future. With a remarkable €10 billion annual revenue and a global team of 500,000 employees serving 170 countries in over 300 languages, we lead in intelligent, digital-first solutions.

As a globally certified Great Place to Work in 72 countries, our culture thrives on diversity, equity, and inclusion. We value your unique perspective and believe that your talent is the missing piece that completes our vision for a brighter, digitally driven tomorrow.

The Opportunity

Data Services enables the development of next-generation AI systems by providing high-quality data solutions that fuel machine learning, generative AI, and advanced analytics at global scale. We partner with Fortune 100 technology leaders to deliver multi-modal datasets, labeling/annotation, data orchestration, model evaluation, and RLHF (Reinforcement Learning with Human Feedback) to power trustworthy, high-performing AI solutions. We are seeking a Principal Data Scientist (AI/ML Ops) to serve as a technical and strategic leader driving AI/ML operational excellence across Data Services. This role will design scalable AI/ML solutions, establish data science best practices, mentor global teams, and shape strategic AI initiatives for some of the world's largest technology enterprises. As a Principal Data Scientist, this role will lead efforts in data-driven innovation, model optimization, and operational deployment of AI/ML solutions, ensuring that remains at the forefront of AI readiness, data quality, and responsible AI practices.

Key Responsibilities

 Lead the design, development, and deployment of cutting-edge AI/ML models for largescale, real-world applications (i.e, NLP, CV, Generative AI, RLHF).

 Establish best practices for AI/ML Ops pipelines, including data acquisition, labeling, model training, monitoring, and continuous improvement.

 Drive R&D initiatives to evaluate emerging techniques (e.g., foundation models, active learning, automated data curation).

 Define the technical strategy for end-to-end AI/ML pipelines, ensuring scalability, robustness, and compliance.

 Partner with engineering and operations teams to integrate ML solutions into production workflows with high availability, low latency, and cost efficiency.

 Develop governance frameworks for model explainability, bias mitigation, and regulatory alignment (i.e, EU AI Act, NIST AI RMF).

 Oversee data strategy for multi-modal datasets (text, audio, video, images), ensuring dataset quality, diversity, and readiness for ML at scale.

 Collaborate with annotation teams and platforms to optimize labeling throughput, quality assurance processes, and SLA adherence.

 Introduce innovative data evaluation metrics beyond accuracy (robustness, fairness, interpretability).

 Engage with executive stakeholders (internal & external) to translate business goals into AI/ML-enabled solutions.

 Provide thought leadership through client workshops, whitepapers, and industry forums, positioning as a trusted AI partner.

 Contribute to revenue growth by influencing AI-driven product strategies and service offerings.

 Mentor and develop junior and senior data scientists, fostering a culture of technical excellence, innovation, and continuous learning.

 Build global communities of practice to standardize AI/ML approaches across 's operations.

Qualifications

 Ph.D. or Master's in Computer Science, Machine Learning, Data Science, or related field.

 8+ years of experience in AI/ML, with 5+ years in deploying ML models in production environments.

 Proven track record in leading large-scale AI/ML projects, particularly in data-intensive environments.

 Programming: Python (NumPy, Pandas, PyTorch/TensorFlow, Hugging Face), SQL, Spark.

 ML Techniques: Deep Learning, NLP, Computer Vision, Generative AI, Reinforcement Learning.

 MLOps & Infrastructure: MLflow, Kubeflow, Airflow, Docker/Kubernetes, CI/CD.

 Cloud Platforms: AWS, GCP, Azure.

 Strong understanding of data labeling, data governance, and responsible AI practices.

Preferred Skills

 Experience leading multi-geo, cross-functional teams in AI/ML Ops environments.

 Thought leadership demonstrated via patents, publications, or conference presentations.

 Business acumen to align AI initiatives with revenue growth and strategic priorities.

Why Join Data Services?

 Shape the Future of AI – Influence how the world's leading enterprises train, evaluate, and deploy safe, high-performing AI systems.

 Operate at Global Scale – Drive multimillion-dollar AI data programs across industries, impacting billions of end users worldwide.

 Be a Thought Leader – Represent as an SME at executive forums, industry conferences, and with Fortune 100 clients.

 Work on Cutting-Edge AI – From RLHF and multimodal annotation to responsible AI frameworks, lead innovation in the most critical areas of AI development.

 Accelerate Your Career – Step into a senior/executive leadership role, shaping strategy, mentoring teams, and influencing the AI ecosystem at scale.