Senior Data Scientist

Nash
San Francisco
Workplace: HybridFull timeFunction: Data Science & Machine LearningSkills: ["Product judgment","Communication","Customer collaboration","Stakeholder management","High agency"]

Build and productionize data science models that improve Nash’s logistics decisioning across pricing, dispatch, carrier selection, ETA prediction, routing, and supply-demand forecasting. Own initiatives from discovery to deployment and measurement, work with large operational and geospatial datasets, and establish evaluation, monitoring, experimentation, and A/B testing. Partner with Product, Engineering, Operations, customers, and leadership to convert ambiguous business goals into measurable outcomes.

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Nash
Nash
1 month ago

Senior Data Scientist

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Source: Company careers pageValidated by: Fursa AI
Last checked: 16 hours agoStatus: Live

Job Summary

Build and productionize data science models that improve Nash’s logistics decisioning across pricing, dispatch, carrier selection, ETA prediction, routing, and supply-demand forecasting. Own initiatives from discovery to deployment and measurement, work with large operational and geospatial datasets, and establish evaluation, monitoring, experimentation, and A/B testing. Partner with Product, Engineering, Operations, customers, and leadership to convert ambiguous business goals into measurable outcomes.
Location: San Francisco
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Identify and scope high-impact opportunities across pricing, cost prediction, dispatch, carrier selection, ETA prediction, routing, and marketplace balancing.
  • •Own data science initiatives from 0→1 discovery through 1→10 iteration, deployment, and performance improvement.
  • •Work with large, messy operational datasets (delivery events, geospatial data, carrier performance, constraints, and SLA outcomes) to build logistics-aware models.
  • •Develop production data pipelines and model integrations using Python, SQL, and Snowflake, and partner with engineers to serve models via APIs, batch pipelines, or real-time decision systems.
  • •Establish evaluation frameworks, monitoring, experimentation, and A/B testing; measure performance against business outcomes like cost, reliability, on-time delivery, and operational intervention.

Pay and Benefits

Perks:Health InsuranceDentalVisionPaid LeaveEquity

Key Requirements

  • •4+ years of experience as a Data Scientist, Machine Learning Engineer, or in a related quantitative role.
  • •Experience in logistics, marketplaces, supply chain, operations research, or a domain with complex real-world constraints.
  • •Track record taking data science projects from problem definition through production and measurement.
  • •Strong proficiency in Python and SQL, with experience working in cloud data warehouses (Snowflake preferred).
  • •Experience building and maintaining production machine learning systems and clear communication with customers or senior stakeholders.
Experience:LogisticsMarketplacesSupply chainOperations research
Skills:Product judgmentCommunicationCustomer collaborationStakeholder managementHigh agency
Tech Stack:PythonSQLSnowflakeAPIsA/B testingDbtAirflow

Company Brief

Nash
Builds AI-powered virtual assistants and agent platforms that help teams automate workflows, surface insights, and accelerate decision-making by integrating with enterprise tools and data sources. Focuses on conversational AI and task automation for business users.
Industry: AI & Machine Learning
Growth: Early Stage Startup
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