Senior Data Scientist (Forecasting)

WAVE GROUP LLC
United States
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$122,500.0
Working hours
Regular working hours
Job source

Tech stack

Python (Programming Language) Machine Learning Software Tools Large Language Models

Requirements

  • 5+ years in data science or quantitative modelling, ideally with time-series forecasting
  • Strong Python & SQL across the full modelling lifecycle (extraction to production)
  • Track record of taking models from notebook to production, monitored and trusted
  • Experience communicating model reliability to non-technical stakeholders
  • Comfortable working from ambiguous starting points

Bonus points for:

  • Logistics or delivery network experience
  • ML experience where it materially improves forecast accuracy
  • Comfortable using AI tools (LLMs, code assistants) to accelerate workflow
  • Experience influencing technical direction as a team scales

Benefits & conditions

  • Private healthcare & dental cover
  • Enhanced parental leave
  • Office lunches

About the company

This company is hands-down the hottest logistics scale up in Europe, taking the industry by storm and growing at an astronomical pace.

Every parcel that moves through their network generates thousands of data points feeding the forecasting engine that powers every operational decision - shifts, dispatch, routing, expansion. The Senior Data Scientist in this role owns a core domain within that engine, sitting in the company’s biggest and most data-rich squad.

If you want to be at the heart of something genuinely transformative, this might be for you.

️ What you’ll be doing:

  • Owning a core domain in the forecasting engine (demand, expansion, parcel intelligence or sortation)
  • Building and maintaining models from exploration through to production deployment
  • Monitoring live model performance and improving accuracy over time
  • Translating problems from Sortation, Middle Mile, Last Mile, Routing and Commercial into DS problems
  • Quantifying model impact on cost per parcel to help prioritise the roadmap

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