Senior Data Scientist — Operations Analytics & ML Lead

Tiger Analytics; St. Louis (MO); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Equal employment opportunity

Job summary

Tiger Analytics is seeking experienced Senior Data Scientists to drive advanced analytics for operations in a fast-growing analytics consulting firm. You will lead ML and DL initiatives, leverage Databricks, and build self-service apps for operations teams to improve maintenance, reliability, and inventory analytics.

Ideal candidates blend machine learning expertise with hands-on data engineering in a healthcare-adjacent domain and are comfortable translating tribal knowledge into data

Qualifications

• Python and PySpark experience with strong SQL is required.
• Proficient with the Databricks platform including Delta Lake, Unity Catalog, Workflows/Jobs, and SQL warehouses.
• Familiarity with AWS (S3, IAM) is a plus.
• Ability to build an app with Streamlit, Dash, or Gradio connected to SQL warehouses/Unity Catalog.
• ML modeling for operations including time-series, forecasting, anomaly detection.
• NLP/LLM experience on unstructured text.
• MLflow for experiment tracking and deployment.

Responsibilities

• Getting EMPRV data into the lakehouse from Oracle or similar sources.
• Maintenance and work-order analytics including backlog, aging, labor/cost, and asset reuse.
• Reliability and asset-health modeling and risk prioritization.
• Materials and inventory analytics including demand forecasting.
• Develop a Databricks App as front end for ops users.
• Text analytics on work-order notes and classification of failure modes.

Skills

Python

PySpark

SQL

Databricks Platform

Delta Lake

Unity Catalog

Workflows/Jobs

SQL warehouses

Delta Live Tables

Lakehouse

AWS

Streamlit

Dash

Gradio

MLflow

NLP/LLM

Tools

Databricks Apps

Streamlit

Dash

Gradio

Job description

Tiger Analytics is seeking experienced Senior Data Scientists to drive advanced analytics for operations in a fast-growing analytics consulting firm. You will lead ML and DL initiatives, leverage Databricks, and build self-service apps for operations teams to improve maintenance, reliability, and inventory analytics.

Ideal candidates blend machine learning expertise with hands-on data engineering in a healthcare-adjacent domain and are comfortable translating tribal knowledge into data