Senior Data Scientist
Job Summary
The Senior Data Scientist will play a pivotal role in developing and implementing state-of-the-art computer vision and time series prediction algorithms to solve business challenges. This position will work closely with cross-functional teams and be instrumental in driving key initiatives.
Responsibilities
- Design and implement machine learning models, with a focus on computer vision and time series prediction, to solve business problems.
- Collaborate with data engineers to build data pipelines, pre-process data, and deploy models at scale.
- Conduct exploratory data analysis to identify patterns, anomalies, and opportunities for leveraging data to create business value.
- Evaluate existing machine learning models and continuously improve their performance through DevOps and CI/CD practices.
- Collaborate with stakeholders to understand business objectives and translate them into data-driven solutions.
- Understand and contribute to data and application architecture, as well as infrastructure fundamentals.
- Mentor junior data scientists and provide thought leadership in the field.
- Present findings and insights to technical and non-technical stakeholders.
- Lead and participate in Agile development processes to ensure timely delivery
of data solutions. - Keep abreast of the latest developments in the field and identify opportunities
for innovation.
Qualifications
- Master’s or Ph.D. in Computer Science, Statistics, or related field.
- Minimum of 7 years experience in data science, with minimum 4 years focused on computer vision.
- Experience with business analysis methodologies like design thinking.
- Proficiency in programming languages such as Python and SQL, and familiarity with software testing practices.
- Proficiency in machine learning frameworks like TensorFlow, Keras, and PyTorch for the design and deployment of advanced models.
- Strong experience in MLOps, DevOps, CI/CD practices, and data and application architecture.
- Strong statistical background, with experience in both supervised and unsupervised learning methods.
- Strong communication skills, both written and verbal.
- Experience with data visualization tools and techniques.
- Familiarity with infrastructure fundamentals in a cloud computing environment like AWS, Azure, or Google Cloud is a plus.