Data Scientist

Area(s) of responsibility Key Responsibilities: Technical Prowess: Technical Architecture: Design and implement scalable data pipelines, machine learning models, and NLP systems.

Code Review and Mentoring: Provide guidance and mentorship to team members on code quality, best practices, and technical challenges.

Research and Innovation: Stay abreast of the latest advancements in deep learning, NLP, and GenAI, identifying opportunities for innovation and improvement.

Deep Learning and NLP Expertise: Model Development: Build and optimize deep learning models using TensorFlow, Theano, or other relevant frameworks.

NLP Solutions: Develop and implement NLP solutions for tasks such as text classification, named entity recognition, sentiment analysis, and language generation.

GenAI Integration: Leverage GenAI tools to enhance existing models and develop innovative solutions for complex language-related problems.

Python and API Development: Python Proficiency: Demonstrate strong programming skills in Python, including expertise in data manipulation, scientific computing libraries, and web frameworks.

API Design and Implementation: Develop RESTful APIs to integrate machine learning and NLP models into existing systems.

Streamlit: Utilize Streamlit for building interactive data applications and dashboards.

Communication and Collaboration: Effective Communication: Clearly articulate technical concepts to both technical and non-technical stakeholders.

Team Collaboration: Foster a collaborative environment within the team and effectively communicate with other departments.

Cross-Functional Collaboration: Work closely with product managers, engineers, and business analysts to understand requirements and deliver impactful solutions.

Education: Master's or Ph.D. in Computer Science, Data Science, or a related field.

Overall 10 – 15 years of experience with 7+ years of experience in data science or machine learning, with a proven track record of delivering production-ready solutions. 2+ years of experience leading technical teams.