Senior AI Data Scientist

at  MiTek USA Inc

JOB DESCRIPTION

Design, develop, optimize, and deploy traditional machine learning and deep learning algorithms, models, and applications.
This role will be hybrid if based near a MiTek office, with the option to be fully remote if not located near a MiTek office.

QUALIFICATIONS:

• Bachelors degree in a related field required
• 5+ years of experience in computer vision, natural language processing, traditional machine learning, statistical analysis, or related domains required
• Proficiency in Python and SQL required
• Proficiency with machine learning, deep learning, and deployment frameworks such as TensorFlow, PyTorch, or Keras, Scikit-learn, Numpy, Pandas, OpenCV, Restful APIs, Docker required
• Deep knowledge of statistical modeling and machine learning modeling required
• Experience developing and deploying models and applications on cloud platforms such as Azure, AWS, or Google Cloud required
• Excellent communication and presentation skills, with the ability to convey complex findings to non-technical stakeholders
• Strong leadership and mentoring abilities
• Strong business acumen and the ability to translate data insights into actionable recommendations

WHAT YOU WILL DO:

• Research and implement state-of-the-art data science techniques for modeling and algorithm development.
• Lead complex end-to-end projects using structured and unstructured data types, including time series data sources.
• Lead, mentor, and coach junior members of the AI team, fostering their professional growth.
• Manage and prioritize multiple projects, ensuring they are completed on time and within budget.
• Create advanced data visualizations and dashboards to communicate effectively.
• Collaborate with cross-functional teams of engineers, product managers, and researchers to deliver high-quality products and services.
• Stay updated with the latest developments and trends in computer vision and artificial intelligence.
• Interact with customers and cross-functional departments to understand project needs and requirements, collect data sets, and convert the business requirements into technical specifications.
• Develop POCs and prototypes (including data explorations) in a fast-paced environment to ensure feasibility, scalability, and accuracy of algorithms and models.
• Educate and evangelize the use of AI among internal and external stakeholders.