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Supply Chain Data Analyst

KPI Solutions Inc

Advanced Solution Development Data Scientist/Senior Data Engineer (Data+AI / Databricks / SQL) – Closed-Loop Design & Pre-Sales Automation 

KPI Solutions is a leading supply chain and warehouse automation integrator helping companies transform distribution operations through intelligent software, robotics, automation, and data-driven solutions.

With expertise spanning WMS, automation, robotics, controls, and systems integration, KPI partners with customers to design and implement scalable solutions that improve throughput, efficiency, and operational performance across distribution and fulfillment environments.

As KPI continues to expand its Advanced Solutions Development organization, we are investing heavily in next-generation technologies that combine automation, analytics, and AI to shape the future of intralogistics and warehouse operations.

About the Role

We are seeking a highly motivated and hands-on Data Scientist / Senior Data Engineer to help build and scale KPI’s Closed-Loop Design Program — an initiative focused on accelerating pre-sales engineering, improving automation design accuracy, and leveraging AI-driven insights across the customer solution lifecycle.

This role sits at the intersection of:

  • Data Engineering
  • Applied AI & Analytics
  • Supply Chain Automation
  • Solution Design

You will work closely with solution architects, engineering teams, and business stakeholders to transform RFPs, customer requirements, and historical project data into intelligent, repeatable outputs that drive faster and more accurate proposal development.

This is an exciting opportunity for someone who enjoys building systems from the ground up, solving complex operational problems, and influencing how advanced automation solutions are designed and delivered.

What You’ll Deliver: High-Impact Use Cases
  • RFP & Specification Intelligence
    Extract requirements, generate compliance matrices, and identify clarifying questions automatically.
  • Cost & ROI Scenario Modeling
    Support data-driven decision-making through option comparisons and sensitivity analysis.
  • Proposal “Fact Pack” Automation
    Create scalable executive summaries and SOW-ready proposal content from governed datasets.
  • Design & Operational Analytics
    Analyze throughput, staffing models, slotting strategies, and replenishment impacts.
  • Benchmark-Driven Solution Guidance
    Leverage historical project data and comparable implementations to guide future designs.
What You’ll Do
  • Build and maintain curated datasets using Databricks (Delta tables, jobs, SQL Warehouses) and SQL-based governed reporting tables.
  • Ingest and manage full pursuit lifecycle artifacts including RFPs, specifications, drawings, and addenda with proper metadata and version control.
  • Develop applied analytics solutions including:
    • Forecasting
    • Scenario modeling
    • Optimization (LP/MILP or practical heuristics)
    • Similarity modeling and benchmarking
  • Publish reliable datasets and insights for Tableau Cloud consumption with consistent business definitions.
  • Establish a closed-loop learning cycle by comparing design assumptions against operational outcomes to continuously improve benchmarks and estimate accuracy.
  • Partner cross-functionally with engineering, analytics, and solution design teams to improve automation decision-making at scale.
What Success Looks Like

In this role, you will help KPI:

  • Accelerate proposal development with intelligent, governed “first draft” solution packs
  • Improve confidence and accuracy in complex automation pursuits
  • Build scalable benchmarking capabilities that improve operational estimates over time
  • Create data products that directly influence automation strategy and customer outcomes

Requirements

Required Qualifications
  • 4+ years of experience in:
    • Data Science
    • Analytics Engineering
    • Applied Machine Learning
      with proven production delivery experience.
  • Strong SQL skills including:
    • Data modeling
    • Query optimization
    • Governance-ready dataset development
  • Hands-on experience with Databricks (Delta Lake, notebooks, jobs, SQL Warehouses) or similar enterprise data platforms.
  • Strong Python experience preferred for:
    • Data preparation
    • Modeling
    • Workflow automation
  • Ability to communicate assumptions, risks, and analytical outcomes clearly to technical and non-technical stakeholders.
Preferred Qualifications
  • Experience in warehouse automation or intralogistics environments:
    • AMRs
    • AutoStore
    • Shuttle systems
    • Sortation
    • WES/WCS platforms
  • Experience with:
    • Forecasting
    • Optimization
    • Simulation / Digital Twin technologies
    • Decision-support analytics
  • Familiarity with document parsing and extraction workflows for RFP/specification processing.
  • Tableau experience including:
    • Curated dataset publishing
    • Dashboard performance optimization

Benefits

What we Offer:
  • Medical Insurance
  • Dental Insurance
  • Vision Insurance
  • Health Care Concierge Service
  • 401(k) Retirement Plan (Pre-tax & Roth)
  • Company paid Basic Life Insurance, Short-Term Disability & Long-Term Disability
  • Voluntary Life & AD&D Insurance
  • Voluntary Accident, Critical Illness & Hospital Indemnity Insurance
  • Pet Insurance
  • Milk Stork Program
  • Wellness Program with gift card redemption and wellness challenges
  • Paid Time Off (Vacation, Sick & 10 Holidays)
  • Training & Development
Why KPI Solutions?

At KPI Solutions, you’ll be part of a team that values innovation, accountability, and continuous improvement. This is more than a reporting role—it’s an opportunity to make a measurable impact on project success and business performance.

KPI Solutions provides equal employment opportunity to all individuals regardless of their race, color, creed, religion, gender, age, sexual orientation, national origin, disability, veteran status, or any other characteristic protected by states, federal, or local law.
Vacancy posted 4 days ago
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