Applied Machine Learning Analyst

About the role

Sovos is looking for an Applied Machine Learning Analyst to join its global support operations team. You will use ML and AI tools to build forecasting models, develop LLM‑powered classification pipelines, and create visual insights that help the business plan staffing and improve service quality.

Key responsibilities

• Build and maintain time‑series forecasting models (e.g., Prophet) for case volume, staffing, and utilization planning.
• Design, implement, and monitor LLM classification pipelines for CSAT analysis, ticket routing, and escalation flagging.
• Develop text‑embedding and vector‑search workflows for semantic case matching and similarity search.
• Write Python scripts for data cleaning, transformation, and visualization using pandas, plotly, and matplotlib.
• Query Snowflake to answer ad‑hoc business questions and validate model outputs.
• Translate model results into clear, non‑technical narratives for operations managers and leadership.
• Collaborate with the Analytics Engineer to ensure clean, reliable data inputs for all models.

Required profile

• 3–5 years of experience as a data analyst, ML analyst, or applied data scientist.
• Strong Python programming skills for data manipulation and visualization.
• Hands‑on experience with Facebook Prophet or a comparable forecasting library.
• Proven ability to work with LLM APIs, including prompt engineering and output validation.
• Familiarity with text embeddings and vector databases such as Pinecone, pgvector, or Snowflake Cortex.
• Solid SQL knowledge, preferably Snowflake.

Required skills

• Python
• Pandas, Plotly, Matplotlib
• Facebook Prophet (or equivalent)
• LLM APIs and prompt engineering
• Text embeddings & vector search (Pinecone, pgvector, Snowflake Cortex)
• SQL (Snowflake)