Senior Data Scientist

• Work hard, have fun environment - We work hard to deliver a fulfilling, exciting workplace environment for each SMG employee. Our teams are composed of smart, talented, curious people who love a good challenge. 
• Values driven culture where we connect, collaborate & co-create.
• Remote first company (fully remote)
• Unlimited PTO   
• Tech provided
• Company sick pay

As a Data Scientist at SMG, this is what you will do:

• Build models on unstructured text and structured survey data
• Design, develop, test, deploy, and monitor AI and ML solutions to power platform features
• Collaborate on software development with data science colleagues and engineers
• Write production-quality Python code exhibiting best practices in reliability, testing, and performance
• Encapsulate and expose data science models so they can be integrated into the SMG platform
• Manage, deploy, and optimize data science applications and models in the cloud (Azure / Snowflake)
• Lead initiatives that are assigned to you and contribute to projects led by others
• Mentor junior team members

You are a perfect match for the role if you have:

• A master’s degree in data science, statistics, computer science, or related field (broadly construed) or equivalent.
• Extensive experience (4+ years) in data science, ML engineering, or ML operations.
• Core technical skills, including:
  • Machine learning: Python + common libraries, classical machine learning models and approaches, model training and evaluation frameworks and metrics, data analysis and visualization, natural language processing transformers models, databases including SQL and noSQL, statistics
  • ML Ops: Github actions, CI/CD, unit and integration testing, application monitoring and logging (Azure metrics, Grafana), Triton / VLLM, caching (Redis), containerization, API deployment, vector databases, asynchronous execution
  • Cloud platform: Microsoft Azure framework (including function apps, data factory, AI foundry, Snowflake
  • AI / LLM: Prompt engineering, function calling, fine-tuning of open-source LLMs, token management, model guardrails, LLM evaluation, throughput and scaling for LLMs, RAG, agentic frameworks (e.g., LangChain / LangGraph), PyTorch, embedding models
• The curiosity and drive to stay on top of new developments in the AI/LLM space.
• The ability to write production-quality Python code with integrated tests, error handling, and monitoring.
• A deep understanding of how to develop, deploy, and scale LLM solutions to ensure reliability, optimize performance, and manage cost.
• The drive to collaborate with product, engineering, and client teams to build and deliver the best products.
• An “end-to-end” data science skillset with a solid understanding of machine learning fundamentals as well as model management, evaluation, and deployment.
• The willingness to speak up, respectfully offering criticism or suggesting alternatives when you have conviction that better options are available.
• The responsibility to be self-directed and eager to take ownership of your assigned projects.
• The ability to communicate your expertise effectively to audiences with varying levels of technical sophistication, both orally and in writing
• A desire to understand business priorities and customer needs.
• Ability to thrive in a dynamic, fast-paced environment with a growth mindset and a commitment to continuous learning.
• Demonstrated ability to drive change and influence stakeholders at all levels of the organization.

About SMG:
To learn more about our customer, employee, and brand experience management (XM) solutions, visit www.smg.com.