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Job Description

This role supports the enhancement of an internal pricing and inventory decision-support tool used by venue operators and site managers. The tool enables users to configure future periods, run pricing scenarios, and apply model-driven recommendations that forecast demand, inventory needs, and financial impact (revenue, gross profit, margin).

Day to day, the Data Scientist will:

• Build and deploy predictive models that power product-level pricing and scenario outputs in the tool.

• Analyze POS sales, back-of-house and warehouse inventory, IoT/telemetry signals, and vendor data.

• Support scenario analysis and “what‑if” comparisons (e.g., price changes, end-of-event markdowns).

• Translate complex model outputs into clear, business-facing recommendations for non-technical users.

• Partner closely with Data Engineers to ensure models are production-ready, scalable, and reliable.

• Produce clean, documented code and lead knowledge transfer for long-term maintainability.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

• 5+ years of experience developing and deploying predictive models in production environments.

• Strong proficiency in Python or R, and SQL.

• Proven experience in:

• Time-series forecasting

• Recommendation systems (pricing, demand, or inventory)

• Anomaly detection

• Modeling with IoT or telemetry data

• Hands-on experience with cloud data warehouses (Snowflake OR Databricks)

• Experience working with retail, inventory, supply chain, or vendor-based datasets. • Experience building models across different venue or event types (sports, concerts, parks).

• Familiarity with model performance metrics, monitoring, and lifecycle management.

• Experience working directly with operations or business stakeholders.

• Background supporting decision tools rather than purely analytical dashboards.