Data Scientist

2 days ago

Bengaluru Karnataka, India Valiance Analytics Full time

Summary:
such as unique footfall counting and face detection/recognition. This role requires a blend
of deep technical expertise, creativity, and practical experience in the field.

Key Responsibilities:
Develop and implement advanced computer vision algorithms for unique footfall
counting, face detection, and face recognition.
Design and build scalable, high-performance models to process and analyze large
volumes of visual data.
Collaborate with cross-functional teams to integrate computer vision solutions into
existing and new platforms.
Conduct research to stay updated with the latest advancements in computer vision
and machine learning technologies.
Optimize and fine-tune models to improve accuracy, speed, and efficiency.
Ensure robust model validation and testing to maintain high standards of reliability
and performance.
Analyze and interpret complex data to provide actionable insights and
recommendations.
Document processes, methodologies, and best practices for future reference and
knowledge sharing.

Qualifications:
Bachelor's or master's degree in computer science, Data Science, Electrical
Engineering, or a related field.
1-3 years of professional experience in data science and computer vision.
Strong proficiency in programming languages such as Python, C++, and relevant
libraries/frameworks (e.g., TensorFlow, PyTorch, OpenCV).
Extensive experience with deep learning techniques and frameworks.
Proven expertise in developing and deploying computer vision models for footfall
counting and face detection/recognition

Solid understanding of machine learning algorithms and statistical analysis.
Experience with large-scale data processing and analysis.
Excellent problem-solving skills and attention to detail.
Strong communication skills with the ability to explain complex technical concepts
to non-technical stakeholders.
Ability to work independently and as part of a collaborative team.

Preferred Skills:
Experience with cloud platforms (e.g., Azure) for deploying and scaling models.
Knowledge of edge computing and deploying models on edge devices.
Familiarity with privacy and security considerations in face recognition
technologies.
Experience with real-time data processing and streaming.

**Qualifications**:
Bachelor's, Master's, or Ph.D. in Computer Science, Electrical Engineering, or a related field.

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