Data Scientist III

• EDUCATION: A Bachelor’s or Master’s degree in a quantitative field (Computer Science, Data Science, Engineering, Mathematics, or related). A Master’s degree is preferred. 

   

• EXPERIENCE: 3–7 years of experience delivering AI and machine learning solutions with measurable business impact. Experience in regulated industries (financial services, insurance, healthcare) is a plus. 

   

• Strong technical command of the tools and languages used to deliver high impact AI/ML solutions into production (Python, PyTorch, Spark, Azure, ADO Pipelines, PowerShell, Kubernetes, Databricks jobs, MLFlow). 

   

• Successfully led the delivery of multiple stable releases in ML and AI domain. 

   

• Solid understanding of machine learning and AI techniques, including classification models, neural networks, NLP, LLMs, RAG architectures, and fine-tuning approaches, and how to apply them effectively to targeted use cases.  

   

• A curious and inquisitive mindset, with the ability to ideate and drive improvements that simplify, modernize, and standardize model architectures and approaches. Experience with MLOps best practices is preferred. 

   

• Unstructured data storage, search, and retrieval (text and images) knowledge is preferred. 

   

• Familiarity with unstructured data systems, search, and retrieval (text and image) is preferred. 

   

• Experience mentoring or supporting other technical team members through collaboration, design discussions, and code reviews, while maintaining a strong individual contributor focus. 

   

• Strong communication skills with the ability to influence engineers, product partners, and leadership. 

   

• Comfort operating with autonomy and accountability in ambiguous, high-impact problem spaces. 

   

 
Key Behaviors of a Successful Candidate 

• Driving Success – Sets goals that inspire others; demonstrates a high level of ambition to achieve outstanding results. 

   

• Improvement Mindset – Identifies the interrelatedness of work activities; targets important areas for improvement across business unit/functions. 

   

• Winning Together - Makes decisions in partnership with impacted business unit/function leaders with the goals of the organization in mind; acts in the best interest of the organization.