Lead Data Scientist

As the Lead Data Scientist in this strategic role, you will be responsible for steering the design and execution of complex data science initiatives. Your primary responsibilities will include: - Leading the end-to-end lifecycle of advanced Gen AI projects, from scoping to delivery and deployment within cross-functional teams. - Defining data science best practices, code quality standards, and technical governance for the team. - Demonstrating expert-level proficiency in Python or R, along with deep experience in data science libraries like pandas, NumPy, Scikit-Learn, TensorFlow, PyTorch, and Keras. - Overseeing the adoption and optimization of Natural Language Processing (NLP) solutions, including frameworks like NLTK, SpaCy, Gensim, and advanced transformer models such as BERT, GPT, LLMs. - Architecting and guiding the implementation of large-scale text analytics systems, including topic modeling, sentiment analysis, text classification, and semantic search. - Ensuring robust model management, reproducibility, and effective MLOps in cloud (AWS, Azure, GCP) and on-premise infrastructures. - Demonstrating advanced SQL and NoSQL expertise, as well as hands-on experience with orchestration and workflow automation tools like Airflow and Control-M. Your secondary responsibilities will involve: - Mentoring and upskilling data scientists, reviewing code and solutions, and providing technical leadership on multiple concurrent projects. - Shaping data flow designs for large-scale, unstructured data while championing data quality and integrity standards. - Driving model validation, monitoring, and continuous improvement for production workloads. In terms of managerial & leadership responsibilities, you will: - Lead and mentor the data science team, setting strategic direction and fostering a collaborative, high-performance culture. - Oversee planning, execution, and delivery of multiple data science projects, ensuring alignment with business objectives and timely completion. - Serve as the primary liaison with stakeholders, translating business needs into actionable data strategies and maintaining data governance standards. Key Success Metrics for this role will include: - Timely and on-budget delivery of high-impact, production-ready models. - Enabling and accelerating innovation in technical projects. - Measurable improvements in team capability and modeling infrastructure reliability. - Business value generation through advanced analytics solutions. As the Lead Data Scientist in this strategic role, you will be responsible for steering the design and execution of complex data science initiatives. Your primary responsibilities will include: - Leading the end-to-end lifecycle of advanced Gen AI projects, from scoping to delivery and deployment within cross-functional teams. - Defining data science best practices, code quality standards, and technical governance for the team. - Demonstrating expert-level proficiency in Python or R, along with deep experience in data science libraries like pandas, NumPy, Scikit-Learn, TensorFlow, PyTorch, and Keras. - Overseeing the adoption and optimization of Natural Language Processing (NLP) solutions, including frameworks like NLTK, SpaCy, Gensim, and advanced transformer models such as BERT, GPT, LLMs. - Architecting and guiding the implementation of large-scale text analytics systems, including topic modeling, sentiment analysis, text classification, and semantic search. - Ensuring robust model management, reproducibility, and effective MLOps in cloud (AWS, Azure, GCP) and on-premise infrastructures. - Demonstrating advanced SQL and NoSQL expertise, as well as hands-on experience with orchestration and workflow automation tools like Airflow and Control-M. Your secondary responsibilities will involve: - Mentoring and upskilling data scientists, reviewing code and solutions, and providing technical leadership on multiple concurrent projects. - Shaping data flow designs for large-scale, unstructured data while championing data quality and integrity standards. - Driving model validation, monitoring, and continuous improvement for production workloads. In terms of managerial & leadership responsibilities, you will: - Lead and mentor the data science team, setting strategic direction and fostering a collaborative, high-performance culture. - Oversee planning, execution, and delivery of multiple data science projects, ensuring alignment with business objectives and timely completion. - Serve as the primary liaison with stakeholders, translating business needs into actionable data strategies and maintaining data governance standards. Key Success Metrics for this role will include: - Timely and on-budget delivery of high-impact, production-ready models. - Enabling and accelerating innovation in technical projects. - Measurable improvements in team capability and modeling infrastructure reliability. - Business value generation through advanced analytics solutions.