Data Scientist Jobs

About The Position

Requirements

• Bachelor’s degree in computer science, statistics, a quantitative discipline, or equivalent practical experience.
• Seven years of experience in software development, applied AI/ML, and statistical analysis.
• Demonstrated track record of rapidly building and shipping software products, rather than only developing models or analyses.
• Working knowledge of machine learning and statistical analysis methods, with experience applying them to business problems.
• Strong software engineering skills and proficiency in Python, including building APIs and backend services.
• Experience with ML design and ML infrastructure, including model deployment, evaluation, data processing, and machine learning frameworks and libraries.
• Hands-on experience with deep learning and LLM application frameworks, including PyTorch, TensorFlow, LangChain, and LangGraph.
• Hands-on experience building generative AI applications, including prompt engineering and retrieval-augmented generation (RAG).
• Advanced degrees in a relevant field may be considered in lieu of a portion of the required experience.

Nice To Haves

• Master’s degree, or a PhD with relevant experience.
• Experience with generative AI research or applications.
• Experience building agent-based systems and working with orchestration frameworks.
• Experience with cloud computing platforms and infrastructure such as Azure, Google Cloud, or AWS, and scalable data processing with SQL or Spark.
• Solid MLOps and LLMOps practices, including CI/CD, monitoring, and model lifecycle management.
• Experience rapidly developing and shipping software in a fast-paced, customer-facing environment while adapting to changing priorities.
• Understanding of responsible AI and governance for regulated or healthcare environments.

Responsibilities

• Develop and deploy novel applications leveraging machine learning and generative AI models, contributing to technical direction for AI, machine learning, and statistical analysis across the organization.
• Design and develop scalable applications—including LLM applications, copilots, agents, and RAG and search—embedded in customer-facing products and enterprise workflows.
• Rapidly prototype new features and iterate based on evaluation results and statistical analysis.
• Contribute to architecture and development of new products and features from 0 to 1.
• Collaborate with researchers and product managers to translate AI and machine learning research into product features.
• Build APIs, services, and data and retrieval pipelines that expose AI and machine learning capabilities to applications.
• Optimize software performance and ensure reliability of deployed applications.
• Apply and promote best practices for building and deploying machine learning and generative AI applications.
• Evaluate model performance using statistical analysis, analyze results, and implement improvements while ensuring responsible and compliant AI.
• Provide technical guidance to less experienced team members and foster a collaborative, high-performing environment.