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PODS
PODS
1,001 – 5,000 Employees
H1B Visa SponsorConstructionHospitalityTravel
PODS is a moving and storage company built around portable, weather-resistant containers delivered directly to customers. Its service supports DIY packing, local and long-distance moves, monthly rentals, and storage at secure, climate-controlled Storage Centers. Customers can choose from multiple container sizes, load at ground level, and arrange optional professional loading and unloading. PODS also offers storage-only solutions, financing options, and online tools for managing a move, creating opportunities across logistics, customer service, operations, technology, and related business functions.
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Data Scientist II Remote in Florida

Join PODS as a Data Scientist II developing optimization, machine learning, and automated workflow solutions. Improve logistics capacity planning, routing, scheduling, and resource allocation through practical operational analytics.

USUnited StatesFLFloridaRemoteFull-timeMiddleSeniorEnglish RequiredData Scientist
AWSCloudPythonSQL

Description

  • Develop and maintain optimization models for capacity planning, routing, scheduling, and resource allocation
  • Translate operational challenges into decision variables, objectives, and constraints
  • Analyze root causes to uncover optimization and automation opportunities across field operations
  • Build, test, and maintain forecasting, regression, classification, and anomaly detection models for operational use cases
  • Prepare and validate datasets, engineer features, and assess model performance
  • Create reproducible data pipelines and automate recurring analyses, model executions, and reports
  • Help establish shared tools, frameworks, and standards that make solutions repeatable
  • Maintain Snowflake data models supporting analysts and downstream applications
  • Build dashboards and decision-support tools that turn analytical findings into action
  • Record model logic, methodologies, and assumptions alongside related tools and pipelines
  • Explain findings, limitations, and recommendations clearly to technical and operational audiences
  • Report to the Director of Operations Data Science & AI while collaborating with engineers and operational stakeholders

Requirements

  • Bachelor’s degree required in a quantitative discipline such as data science, statistics, operations research, industrial engineering, applied mathematics, physics, computer science, engineering, economics, or a related field
  • Master’s degree preferred
  • At least 3 years of experience in applied data science, machine learning, or quantitative analytics
  • Relevant internships, co-ops, or graduate research may satisfy part of the experience requirement
  • Practical experience formulating and solving mixed-integer linear programming models
  • Experience with Gurobi, Pyomo, OR-Tools, PuLP, CPLEX, or a comparable optimization library or solver required
  • Advanced SQL skills with a modern cloud data warehouse, preferably Snowflake
  • Proficiency in Python for data analysis and model development
  • Experience developing, testing, and validating forecasting, regression, classification, or other predictive models
  • Experience creating reproducible data pipelines and automating recurring analyses and model workflows
  • Ability to communicate analytical and model results through clear visualizations and usable decision-support tools
  • Ability to explain methods and results clearly and document work for reproducibility and review
  • Ability to convert loosely defined operational challenges into focused analytical questions and practical solutions
  • Experience or academic training in machine learning and mathematical optimization
  • Familiarity with cloud data platforms such as Snowflake or AWS
  • Experience supporting operations, supply chain, logistics, or another capacity-constrained business is preferred
  • Ability to sit at a desk and work on a computer for up to 8 hours per day
  • Ability to use hands and fingers for keyboarding and mouse navigation
  • Vision adequate for viewing small details on a computer monitor
  • Ability to stand and walk for up to 8 hours per day, stoop, bend, and lift boxes weighing up to 50 pounds
  • Ability to hear and communicate verbally through a telephone handset or connected headset
  • Regular attendance and punctuality are required
  • Employment may require criminal background and/or drug screening before hire, plus random drug screening under company policy

Benefits

  • Full-time remote position
  • Climate-controlled office setting during standard business hours
  • Standard business hours
  • Minimal travel required

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