Responsibilities:

• Assist in the design and implementation of machine learning models, particularly in the areas of computer vision and time series prediction.
• Work with senior data scientists and data engineers to contribute to data pipeline construction, data preprocessing, and model deployment at scale.
• Perform exploratory data analysis to identify patterns, anomalies, and opportunities for leveraging data.
• Support the evaluation and ongoing refinement of existing machine learning models, following DevOps and CI/CD best practices.
• Collaborate with business and technical stakeholders to understand objectives and contribute to data-driven solutions.
• Assist in enhancing the data and application architecture, as well as infrastructure fundamentals.
• Learn from senior team members and share knowledge with junior data scientists or interns.
• Present findings and insights to internal teams.
• Participate in Agile development sprints and contribute to ongoing projects in a collaborative manner.
• Stay updated on the latest trends and technologies in the data science field.

Qualifications:

• Master’s or Bachelor’s in Computer Science, Statistics, or related field.
• Minimum of 3 – 6 years experience in data science, with minimum 2 years focus on computer vision.
• Familiarity with business analysis methodologies, such as design thinking, is a plus.
• Experience with machine learning frameworks such as TensorFlow, or Keras, or PyTorch.
• Proficiency in Python and SQL, and some experience with software testing.
• Exposure to DevOps and CI/CD practices is beneficial.
• Good statistical understanding, with experience in supervised and unsupervised learning methods.
• Effective communication skills, both written and verbal.
• Some experience with data visualization tools and techniques.
• Familiarity with cloud computing environments like AWS, Azure, or Google Cloud is a plus but not required.