Data Scientist 4

Overview

Data Scientist 4 in the Office of the CTO, building scalable AI and machine learning solutions that help teams make faster, smarter decisions.

What you'll do

• Design, develop, and deploy end-to-end AI/ML and Generative AI solutions that support critical business needs.
• Build scalable machine learning architectures and evaluate modern tools, frameworks, and platforms to strengthen the data science ecosystem.
• Develop production-ready models and deliver solutions on cloud environments (preferably Azure) using strong MLOps practices.
• Partner closely with data scientists, engineers, and business stakeholders to translate business problems into technical solutions with measurable impact.
• Lead technical design discussions, guide teams through complex AI/ML challenges, and foster a collaborative innovation culture.
• Establish monitoring, governance, and fail-safe mechanisms to ensure model reliability and continuous improvement.
• Deliver rapid POCs and extract meaningful insights from diverse and complex datasets.

What you'll need

• Strong programming skills in Python or R and expertise with ML/DL frameworks.
• Experience with cloud platforms (Azure, AWS, or GCP) and big-data technologies (e.g., Hadoop, Spark).
• Proven understanding of MLOps, model deployment, and ML fail-safe principles.
• Hands-on experience in leading projects using agile methodologies.
• Strong communication and stakeholder management skills.
• 8–12 years of experience delivering enterprise-scale data science and AI/ML solutions.
• Bachelor's, Master's, or Ph.D. in Computer Science, Data Science, Engineering, or a related field.

Nice to have

• Experience designing large-scale AI/ML or GenAI architectures.
• Background in building highly scalable production ML systems.
• Familiarity with advanced statistical modelling and applied machine learning techniques.
• Experience guiding teams in high impact technical environments.

Details

• Standard business hours with flexibility to collaborate across teams.
• Hybrid role: On-site Flex (3+ days per week on-site with the balance remote) or Virtual Flex (1-2 days per week on-site, remote the rest).