Cutting Edge Data Scientist Leader

1 day ago

Gurgaon, Haryana, India beBeeDataScience Full time ₹ 20,00,000 - ₹ 25,00,000
Lead Data Scientist

About the Role

We are seeking an exceptional Lead Data Scientist to own the vision and delivery of enterprise-scale data science solutions. As a key member of our team, you will shape the data science strategy, champion best practices, mentor junior data scientists, and drive production-ready AI/ML products from ideation through deployment.

This is a leadership role that requires strong technical expertise in developing and deploying large-scale machine learning pipelines, as well as excellent communication and collaboration skills. You will work closely with cross-functional stakeholders to align on project goals, timelines, and SLAs.

Key Responsibilities

  1. Shape and execute the data science roadmap for ML, GenAI, and ASR, including tooling, methodologies, and best practices.
  2. Architect, develop, and deploy large-scale ML and GenAI pipelines, including Voice Activity Detection (VAD), Speaker Diarization, and ASR models.
  3. Own the full data science lifecycle, from opportunity identification and requirement gathering to modeling, deployment, monitoring, and optimization.
  4. Drive MLOps practices, including CI/CD for models, feature stores, monitoring, and automated rollback strategies.
  5. Mentor and develop junior and mid-level data scientists, fostering a culture of continuous learning and collaboration.

Requirements

  • 8+ years of hands-on experience in Data Science/AI, with at least 3 years in a senior or leadership role.
  • Proven expertise in developing and deploying ASR systems, including training models (e.g., Whisper), designing VAD pipelines, and implementing Speaker Diarization (e.g., Pyannote).
  • Deep knowledge of large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning, and embedding-based retrieval.
  • Expert proficiency in Python and its core libraries, including NumPy, Pandas, SpaCy, scikit-learn, PyTorch/TF 2, and Hugging Face Transformers.
  • Strong understanding of ML & deep learning architectures like NLP transformers and GNNs.
  • Experience with orchestration and deployment tools such as Docker, Kubernetes, Airflow, and cloud services (AWS/GCP/Azure).

Good to Have

  • A Master's or Ph.D. in a related technical field (Computer Science, Statistics, etc.).
  • Prior experience in the Economics/Financial industry.

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