Lead Data Scientist || GEN-AI, LLM, NLP, Conversational AI |

Role Overview:

We' re looking for a Lead Data Scientist to join our fast-growing, mission-driven team. This is a high-impact leadership role at the intersection of technology, strategy, and innovation where your expertise will power intelligent solutions that redefine how we think about data, products, and customer experience.

If you thrive in high-performance environments and want to lead cutting-edge projects with Generative AI, LLMs, and large-scale NLP systems, this is your opportunity to make a lasting impact.

Key Responsibilities:

Build the Future with AI/ML

• Architect scalable AI systems to solve real-world, high-value business challenges cross domains.
• Design and deploy cutting-edge solutions with Generative AI, Transformer architectures, and custom Large Language Models (LLMs).
• Apply state-of-the-art ML techniques prompt engineering, transfer learning, multi-modal learning to push the boundaries of what's possible.

NLP at Scale

• Lead the development of advanced NLP systems: semantic search, question answering, summarization, classification, and conversational AI.
• Work with best-in-class models and libraries: BERT, GPT, RoBERTa, Word2Vec, SpaCy, NLTK, Hugging Face Transformers, and more.
• Leverage language understanding to transform unstructured data into strategic insights.

Full-Lifecycle Model Deployment

• Build robust MLOps pipelines for training, testing, deployment, and monitoring using MLflow, Kubeflow, Airflow, and CI/CD tools.
• Containerize and orchestrate AI models using Docker and Kubernetes across cloud environments (AWS, GCP, Azure).
• Design APIs and inference services using FastAPI or gRPC, optimized for performance, scalability, and uptime.

Lead, Inspire, and Elevate

• Build and mentor a world-class data science team, nurturing talent and fostering a culture of curiosity, experimentation, and technical excellence.
• Drive the data science strategy, influence key decisions, and align AI initiatives with business goals.
• Establish best-in-class practices for model development, code quality, documentation, and performance evaluation.

Data at the Core

• Work hands-on with structured, semi-structured, and unstructured data.
• Optimize high-volume data pipelines, integrate with SQL and NoSQL databases, and leverage big data ecosystems like Spark, Hive, and Hadoop.
• Use statistical modeling and experimental design to derive actionable intelligence from data

Collaborate Across the Enterprise

• Work closely with engineering, product, and executive teams to define problems, explore solutions, and deliver AI products that move the needle.
• Translate technical concepts into strategic recommendations and insights that influence roadmaps and revenue.
• Champion AI literacy and advocate for ethical, explainable, and scalable data science across the organization.

Education

• Bachelors or Master’s in Computer Science, AI, Data Science, Machine Learning, Engineering, or a related technical discipline. PhD is a plus.
  

Experience

• 6+ years of experience in data science or machine learning, with 2+ years in a leadership or managerial role.
  
• Proven record of building and deploying AI solutions at scale in real-world production environments.
  
• Experience in GenAI, NLP, cloud-native architectures, and full-cycle ML development.
  

Technical Expertise

• Languages & Libraries: Python, Scikit-learn, PyTorch, TensorFlow, Hugging Face, NumPy, Pandas
  
• NLP: BERT, GPT, Word2Vec, SpaCy, NLTK, TextBlob, CoreNLP, Transformer-based architectures
  
• Cloud & Deployment: AWS, Azure, GCP, Docker, Kubernetes, FastAPI, gRPC
  
• Big Data: Spark, Hive, Hadoop, Kafka
  
• Data Systems: PostgreSQL, MongoDB, Cassandra, Snowflake, BigQuery
  
• MLOps & Monitoring: MLflow, Airflow, Kubeflow, Prometheus, Grafana
  

Nice to Have

• Experience in online reputation management, customer analytics, or product-led organizations.
  
• Familiarity with responsible AI, fairness, and explainability techniques (SHAP, LIME).