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.

Qualifications

• Education: Master's or Ph.D. in Computer Science, Data Science, or a related field.
• Experience:
• 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.
• Strong expertise in Python, deep learning frameworks (TensorFlow, Theano), NLP libraries (spaCy, NLTK, Hugging Face), and GenAI tools.
• Experience with API development (Flask, FastAPI) and Streamlit)

Preferred Skills

• Cloud Platforms: AWS, Azure, GCP
• Big Data Technologies: Spark, Hadoop
• MLOps: Experience with model deployment, monitoring, and continuous integration/continuous delivery (CI/CD) pipelines.