CTO_ML/DL Data scientist

7 Months ago • All levels • Data Analysis

Job Summary

Job Description

This role involves designing, developing, and deploying machine learning and deep learning models to solve complex business problems. Responsibilities include data analysis, collaboration with cross-functional teams, system architecture, mentoring junior data scientists, staying current with industry trends, and evaluating emerging technologies. The Senior Data Scientist will lead a team, providing mentorship, overseeing design and architecture, conducting code reviews, and balancing leadership with hands-on development. Strong problem-solving and communication skills are essential.
Must have:
  • Design & Develop ML/DL Models
  • Data Analysis & Interpretation
  • Collaborate with Cross-Functional Teams
  • System Architecture & Design
  • Mentorship & Guidance
  • Team Management
Good to have:
  • Experience with Transformer Models
  • Experience with Graph Neural Networks

Job Details

About the job

Job Description

Machine Learning/Deep Learning Senior Data Scientist

Job Summary:

We are seeking an experienced Machine Learning/Deep Learning Senior Data Scientist to join our team and drive the development of cutting-edge AI solutions. As a Senior Data Scientist, you will be responsible for designing, developing, and deploying scalable and efficient machine learning and deep learning models to solve complex business problems. You will work closely with cross-functional teams to ensure the successful delivery of AI-powered projects.

Key Responsibilities:

  • Design and Develop Machine Learning/Deep Learning Models: Design, develop, and deploy machine learning and deep learning models using various techniques such as supervised, unsupervised, and reinforcement learning.
  • Data Analysis and Interpretation: Analyze and interpret complex data to identify patterns, trends, and insights that inform business decisions.
  • Collaborate with Cross-Functional Teams: Work closely with data engineers, DevOps engineers, and QA engineers to ensure seamless integration of machine learning and deep learning models into larger systems.
  • Architecture and Design: Design and architect scalable and efficient machine learning and deep learning systems, ensuring scalability, efficiency, and maintainability.
  • Mentorship and Guidance: Mentor and guide junior data scientists, providing technical guidance and best practices for machine learning and deep learning development.
  • Staying Up-to-Date with Industry Trends: Keep up-to-date with the latest developments in machine learning, deep learning, and related technologies, applying this knowledge to drive innovation and improvement.
  • Evaluate and Implement Emerging Technologies: Evaluate and implement emerging technologies such as transformer-based models, graph neural networks, and other advanced techniques to stay ahead of the competition.

Team Management Responsibilities:

  • Team Management: Lead a team of engineers, providing mentorship and guidance.
  • Design and Architecture: Oversee design and architecture decisions.
  • Code Reviews: Conduct code and design reviews.
  • Individual Contribution: Balance leadership with hands-on development.

Soft Skills:

  • Problem-Solving: Efficiently resolve technical issues.
  • Communication: Strong verbal and written communication skills.
  • Continuous Learning: Passion for learning new technologies and frameworks.

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