Data Science Team Lead

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Position Overview:

This leader is responsible for directing the data science team in the creation of foundational AI models and actionable data insights that are essential for powering the agentic AI solutions, with a primary focus on leveraging the tools and services within Google Vertex AI.

Duties and Responsibilities:

• Provide strong leadership and effective management to a team of skilled data scientists and AI researchers, fostering a collaborative and innovative environment within the Vertex AI ecosystem.
• Clearly define data requirements for AI model development and work closely with the ERP Integration team to ensure seamless accessibility and high quality of data within Google Cloud Storage, BigQuery, and other relevant data stores.
• Oversee the entire lifecycle of machine learning model development for critical Natural Language Processing (NLP) tasks such as intent recognition, entity extraction, sentiment analysis, and other tasks crucial for agentic interactions, ensuring the effective utilization of Vertex AI’s pre-trained models and custom training capabilities.
• Actively drive research and experimentation efforts involving cutting-edge AI/ML techniques and advanced models, with a specific focus on exploring and implementing Large Language Models (LLMs) readily available on the Vertex AI platform (e.g., PaLM 2, Gemini).
• Establish and enforce rigorous standards for the reproducibility and methodological soundness of all data science workflows conducted within the Vertex AI environment, promoting best practices in experimentation and validation.
• Collaborate closely with the Agent Engineering team to ensure the seamless integration of developed AI models into the operational agentic systems deployed on Vertex AI Endpoints.
• Define relevant performance metrics and implement robust monitoring systems to track the effectiveness and accuracy of AI models deployed via the Vertex AI Model Registry and Endpoints.
• Maintain a comprehensive understanding of the latest trends and advancements in data science methodologies, tools, and the continuously evolving features of Google Vertex AI.

Essential Skills & Experience:

• Python: Expert-level proficiency.
• Data Science Libraries: Extensive experience with NumPy, Pandas, SciPy, scikit-learn, TensorFlow, PyTorch, Transformers, spaCy, NLTK.
• Google Cloud Platform (GCP): In-depth experience with Vertex AI Workbench, Vertex AI Training (custom and pre-built containers), Hyperparameter Tuning, Vertex AI Experiments, Vertex AI Feature Store (if applicable), Vertex AI Model Registry, Vertex AI Endpoints, and proficient use of the Vertex AI SDK (Python).
• Data Storage & Processing: Strong experience with BigQuery and Cloud Storage; familiarity with Dataflow is a plus.
• Large Language Models (LLMs): Practical, hands-on experience with fine-tuning, evaluating, and deploying LLMs, specifically utilizing Vertex AI’s LLM capabilities (PaLM 2, Gemini).
• MLOps: Solid understanding of Machine Learning Operations (MLOps) principles and practical experience using Vertex AI MLOps tools for model lifecycle management.
• Version Control: Proficient in using Git for collaborative development.
• Significant and demonstrable experience (5+ years) in the complete lifecycle of developing and successfully deploying machine learning models within a business setting, with a strong and demonstrable focus on the Google Cloud Platform and its Vertex AI services.
• Expert-level proficiency in the Python programming language and extensive experience with key data science libraries, including NumPy, Pandas, SciPy, scikit-learn, TensorFlow, PyTorch, and NLP-specific libraries such as spaCy and the Transformers library (Hugging Face), with a strong preference for practical experience using these within the Vertex AI environment and its SDK.
• Substantial hands-on experience with a wide range of Natural Language Processing (NLP) techniques and Large Language Models (LLMs), with specific expertise in leveraging Vertex AI’s NLP capabilities.
• Exceptional analytical and problem-solving skills, with a proven ability to translate complex business challenges into data-driven solutions.
• Strong leadership and interpersonal communication skills, with the ability to effectively guide and mentor a team of data scientists.
• Highly Desirable: Proven experience working with Google Cloud Platform data storage and processing services, including BigQuery and Cloud Storage.
• Preferred: Relevant Google Cloud Professional certifications (e.g., Data Engineer, Machine Learning Engineer).

Educational Requirements:

• Master’s or Ph.D. degree in Data Science, Machine Learning, Statistics, Computer Science, or a closely related quantitative field.

Professional Experience:

• 5+ Years

Work Location:

Mumbai