Mixed Integer Programming

Mixed Integer Programming Data Jobs

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Today

AI Engineer - Allocation and Packing Systems

Gallatin El Segundo, CA

El Segundo, CA

Today

$80k - $210k/yr Full time Python Artificial Intelligence Capacity Planning

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Job Description

Gallatin is hiring an AI Engineer to build and implement packing and allocation models and algorithms for transport assets. The role focuses on translating optimization outputs into resupply and routing workflows while ensuring generated plans remain physically feasible under operational constraints.

Responsibilities

Build, maintain, and implement packing and allocation models for transport assets.
Encode constraints including volume, weight, compatibility, sequencing, and asset usage.
Balance packing efficiency against runtime and real-world operational constraints.
Develop and refine heuristics or exact methods for solving packing and allocation problems.
Scale packing solutions across large fleets and dynamic inputs.
Evaluate tradeoffs between optimality, speed, and explainability.
Own data inputs that drive allocation and packing, including asset and supply attributes.
Validate, normalize, and maintain packing-related datasets.
Handle edge cases and incomplete data directly.
Integrate packing outputs into resupply and routing workflows.
Collaborate with other teams to confirm physical executability of outputs.
Validate solutions using scenario testing and operational feedback.
Ensure AI-generated plans cannot bypass feasibility or constraint enforcement layers.

Requirements

Strong programming skills in Python or similar, with experience translating allocation logic into deterministic, testable production code.
Strong foundation in operations research, optimization, or applied algorithms for resource allocation and physical feasibility.
Background in operations research, applied math, industrial engineering, or related fields.
Familiarity implementing allocation and assignment algorithms, including matching, prioritization, and constraint-based allocation under competing demands.
Experience modeling and solving packing problems such as bin packing, knapsack, or multidimensional (2D/3D) packing.
Ability to encode capacity, compatibility, priority, and physical constraints within allocation and packing systems.
Familiarity with optimization techniques including linear programming, mixed-integer programming, or heuristic and approximation methods for NP-hard problems.
Experience balancing solution quality, feasibility, and computational performance in large-scale or time-sensitive systems.
Experience with vehicle loading or palletization problems.
Ability to reason about physical constraints and edge cases.
Comfort owning data pipelines and assumptions end-to-end.
Strong attention to correctness and failure modes.

Technologies

Python
Linear programming
Mixed-integer programming
A/B testing
Causal inference

Benefits

Competitive compensation commensurate with experience
Generous equity grant
Full healthcare coverage
401k
Unlimited PTO

Bonus Points

Experience integrating packing with simulation systems.
Prior exposure to defense or government planning environments.
Experience with machine learning models, experimentation (including A/B testing), and causal inference.

Compensation Range

$80,000 - $210,000 USD per year.

Security Clearance / U.S. Government Classified Environment

This position may require the ability to obtain and maintain a U.S. government security clearance. The successful candidate must be able to work in a classified environment when necessary.

Citizenship Requirement

U.S. citizenship is required for all positions at Gallatin. Proof of citizenship will be required prior to employment if selected.

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1mo ago

Sr. Data Scientist, Ops Research

MCKESSON Irving, TX

Irving, TX

1mo ago Closed

$136k - $227k/yr Full time Azure Ml Big Data Cloud Platform

This position is no longer accepting applications (closed Sep 6, 2026).

Job Description

Build stochastic process simulation and optimization products to improve supply chain operations within McKesson’s Enterprise Data Science team.

Responsibilities

Develop and apply digital twins and simulation/optimization frameworks to support decisions across supply chain areas including inventory, transportation, and labor planning.
Translate simulation and optimization outputs into actionable recommendations for business partners.
Architect, implement, and drive adoption of stochastic process simulation and optimization solutions; measure impact and make significant improvements to existing solutions.

Requirements

Demonstrated experience developing stochastic process simulations to inform business decisions in inventory, transportation, or other supply chain-related domains.
Strong foundation in probability and statistics, including random variables, probability distributions, hypothesis testing, regression, and modern machine learning methods.
Demonstrated experience in data wrangling using SQL.
Experience with statistical modeling in Python and/or R.
Ability to communicate results to technical leaders and non-technical executive audiences.
Degree or equivalent, typically requiring 7+ years of relevant experience.

Tools & Technologies

SQL, Python, R
Optimization solvers: CPLEX, Gurobi, Xpress, CBC, GLPK
Data and ML platforms: Databricks, Snowflake, Azure ML

Preferred Skills

Experience with commercial or open-source optimization solvers (e.g., CPLEX, Gurobi, Xpress, CBC, GLPK).
Familiarity with reinforcement learning or approximate dynamic programming techniques.
Experience developing dashboards, applications, or decision-support tools that expose model outputs to business users.
Exposure to financial modeling, cost optimization, or pricing analytics.
Experience working in modern data and ML platforms such as Databricks, Snowflake, and Azure ML.

Location & Compensation

Location: Irving, TX (onsite)
Base pay range: USD 136,300 - 227,100 per year

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Mixed Integer Programming Data Jobs

AI Engineer - Allocation and Packing Systems

Sr. Data Scientist, Ops Research

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