Manager, Data Science & Research

About the role

We are looking for a Manager, Data Science & Research to lead a team of experienced Data Scientists while staying hands‑on with model development. The role combines technical execution (≈70% coding) with strategic direction for large‑scale content classification systems across social platforms, web and apps.

Key responsibilities

• Lead development of content classification systems across social platforms (Meta, TikTok, YouTube), web and apps.
• Design and build models for computer vision, NLP and multimodal pipelines.
• Own the full ML lifecycle: data selection, labeling strategy, training, evaluation, and deployment.
• Develop efficient data curation and labeling strategies, including active learning, auto‑labeling and large‑scale sampling.
• Improve model quality while balancing precision/recall, cost, latency and scale.
• Drive automation systems such as auto‑labeling, auto‑curation and retraining loops.
• Apply modern AI approaches including LLMs, embeddings and foundation models to production problems.
• Mentor senior Data Scientists, set technical direction and collaborate with ML Engineering, Product and Policy teams.

Required profile

• Minimum 3 years of experience leading Data Science or ML teams.
• At least 6 years of hands‑on machine learning / deep learning experience.
• Strong background in computer vision and/or natural language processing.
• Proven track record building and deploying production ML systems at scale.
• Deep understanding of real‑world trade‑offs among accuracy, cost and latency.

Required skills

• Python programming.
• Deep learning frameworks: PyTorch and TensorFlow.
• Machine learning libraries: scikit‑learn, OpenCV, HuggingFace.
• Experience with large datasets and model evaluation pipelines.
• Knowledge of active learning, auto‑ML and data‑centric AI techniques.
• Familiarity with LLMs, embeddings and foundation models.