Data Scientist

Responsibilities

• Working with the data science team to research, develop, evaluate, and optimize various computer vision and deep learning models for different problems.
• Explore and analyses unstructured data like images through image processing.
• Take ownership to drive computer vision solutions and meet customer requirements.
• Deploying developed computer vision models on the cloud after optimization to meet customer requirements and maintain them to improve to address additional customer requirements in the future.
• Work closely with teammates to identify issues and use data to propose solutions for effective decision-making.
• Use machine learning tools and statistical techniques to produce solutions to problems.
• Maintain clear and coherent communication, both verbal and written, to understand data needs and report results.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Develop processes and tools to monitor and analyses model performance and data accuracy.
• Undertaking data collection, pre-processing, and analysis.
• Building machine-learning models to address business problems.
• Presenting information using data visualization techniques.
• Combine machine-learning models through ensemble modelling.
• Build predictive machine-learning models and algorithms.
• Processing, cleansing, and validating the integrity of data to be used for analysis.
• Experience in database interrogation and analysis tools.
• Experience using statistical computer languages (Python) to manipulate data and draw insights from large datasets.

Requirements

• Have a degree in Computer Science, Data Science, and Machine Learning or in related fields.
• Understanding about depth and breadth of computer vision and deep learning algorithms.
• At least 2 years of experience in computer vision and/or deep learning for object detection and tracking along with semantic or instance segmentation in the academic or industrial domain.
• Experience with any Machine / Deep Learning Frameworks like Tensor Flow, Keras and PyTorch.
• Experience in training models through GPU computing using NVIDIA CUDA or on the cloud.
• Ability to transform research articles into working solutions to solve real-world problems.
• Proficiency in Python and related packages like NumPy, scikit-image, PIL, OpenCV, matplotlib, seaborn, etc.
• Must be able to produce solutions independently in an organized manner and be able to work in a team when required.
• Must have good Object-Oriented Programming & logical analysis skills in Python.

Preferred (not mandatory to have all)

• Strong foundation in data structures and algorithms in Python.
• Proficiency with AWS cloud computing environments.
• Experience in Agile Application Development and Scrum methodologies to develop efficient, maintainable, readable and production-ready pipelines.

Deep understanding of Software Development Life Cycle (SDLC).