Lead Data Scientist (GenAI | LLM | NLP | Conversational AI )

Lead Data Scientist

This pivotal role offers the unique opportunity to shape data-driven strategies, lead groundbreaking AI initiatives, and mentor a high-performing team of data scientists. If you're ready to make a significant impact, we invite you to explore this exciting opportunity.

As the Lead Data Scientist, you’ll work at the intersection of innovation and business impact, spearheading AI/ML solutions that address complex challenges. This role not only requires exceptional technical expertise but also the ability to inspire and lead a talented team, driving excellence in every project.

Key Responsibilities

1. Leadership & Mentorship

• Lead, inspire, and mentor a team of data scientists, fostering a culture of collaboration, innovation, and continuous learning.
• Provide technical guidance to ensure the delivery of high-quality, scalable solutions within tight deadlines.
• Promote best practices, drive knowledge sharing, and encourage cross-functional collaboration to achieve organizational goals.

2. AI/ML Solution Development

• Architect and deploy scalable, enterprise-level AI solutions tailored to solve complex business problems.
• Engineer and optimize Generative AI models (GenAI), Large Language Models (LLMs), and Transformer-based architectures for top-notch performance.
• Utilize techniques like prompt engineering, transfer learning, and model optimization to deliver state-of-the-art AI solutions.

3. Natural Language Processing (NLP)

• Design advanced NLP solutions leveraging tools such as Word2Vec, BERT, SpaCy, NLTK, CoreNLP, TextBlob, and GloVe.
• Perform semantic analysis, sentiment analysis, text preprocessing, and tokenization to generate actionable business insights.

4. Cloud & Deployment

• Build and deploy AI/ML solutions using frameworks like FastAPI or gRPC for seamless delivery of services.
• Leverage cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP) to design high-performance, scalable systems.
• Deploy models using Docker containers on Kubernetes clusters for optimal scalability and reliability.

5. Database Management

• Manage and optimize large-scale data processing using SQL and NoSQL databases.
• Ensure seamless data flow and retrieval, enhancing overall system performance.

6. Big Data & Analytics

• Utilize big data technologies like Hadoop, Spark, and Hive for analyzing and processing massive datasets.
• Apply statistical and experimental design techniques to uncover meaningful insights and drive decision-making.

7. MLOps & CI/CD Pipelines

• Develop and maintain robust MLOps pipelines to streamline the integration, testing, and deployment of machine learning models.
• Ensure the scalability, reliability, and efficiency of AI/ML models in production environments.

8. Collaboration & Communication

• Partner with product managers, business analysts, and engineering teams to identify challenges and propose innovative solutions.
• Translate complex technical insights into actionable recommendations for technical and non-technical stakeholders alike.

Key Qualifications

Educational Background

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.

Experience

• 5–8 years of industry experience, with a minimum of 2 years in a leadership role managing and mentoring data science teams.
• Proven track record in delivering end-to-end AI/ML solutions that solve real-world business challenges.

Technical Skills

• Proficiency in Python and its data science libraries.
• Advanced expertise in NLP tools like Word2Vec, BERT, NLTK, SpaCy, TextBlob, CoreNLP, and GloVe.
• Strong knowledge of Transformer-based architectures and Generative AI/LLMs.
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and deployment technologies (FastAPI, gRPC, Docker, Kubernetes).
• Proficiency in big data tools (Hadoop, Spark, Hive) and database systems (SQL/NoSQL).
• Strong grasp of statistical methods, machine learning algorithms, and experimental design principles.

Domain Knowledge

• Prior experience in Online Reputation Management or product-based industries is highly desirable.

Additional Skills

• Exceptional project management skills with the ability to manage multiple priorities simultaneously.
• Excellent communication and storytelling skills to convey complex technical concepts effectively to diverse audiences.