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Analytics Engineer

Salary

USD $100,000.00 – $110,000.00

Location

Orlando, FL

Posted

Yesterday

This role is ideal for a high‑potential, early‑career data professional who wants to grow into an Analytics Engineer role. You will start with foundational analytics work—cleaning data, building basic models, and supporting dashboards—while being mentored by senior team members.

This is a hybrid position that requires the employee to work on-site three days per week.

Responsibilities

You’ll help build and maintain data assets that support Finance (forecasting, variance analysis, program financial health) and Procurement / Supply Chain (cycle time, supplier performance, inventory and readiness). Over time, you’ll be exposed to increasingly complex modeling (forecasting, optimization, risk scoring) and modern data practices.

Key responsibilities

  • Data Foundations & Preparation (25%)
  • Dashboards, Reporting & Automation (25%)
  • Finance Analytics Support (20%)
  • Procurement & Supply Chain Analytics Support (20%)
  • Learning & Growth into Data Science / AI

Minimum qualifications

  • Education: Equivalent experience from which comparable knowledge and job skills can be obtained may be substituted for education, if degree is required.
  • Bachelor’s degree in quantitative or related discipline (e.g., Data Analytics, Statistics, Mathematics, Computer Science, Finance, Supply Chain, Industrial Engineering) or equivalent hands-on experience.

Experience

  • At least 3 years of experience in a data related role or strong portfolio of projects.
  • Experience with (some or all) regression analysis, Clustering/Classification models, ML algorithms, and Gradient Boosted Tree models or any forecasting or optimization projects.
  • Ability to demonstrate proficiency in:
  • SQL for queries, joins, common table expressions and window functions.
  • Microsoft Excel for basic analysis (lookup functions, pivots, etc.).
  • PowerBI
  • Familiarity with at least one analytical or scripting language (Python preferred) for data wrangling and EDA.
  • Ability to build basic dashboards or reports in a BI tool (e.g., Power BI (preferred), Tableau, or similar).
  • Familiarity with the SDLC is a nice-to-have.
  • Knowledge of .NET, Angular, HTML/CSS are nice-to-have.
  • Experience with application frameworks such as Flask or Shiny for Python are nice-to-have.

Other requirements

  • Demonstrated curiosity and desire to learn advanced analytics, data science, or AI techniques.
  • Strong analytical mindset.
  • Comfortable working with messy, real-world data.
  • Able to interpret trends and communicate findings clearly in writing and presentations.

Skills and technology used

  • Python
  • PowerBI
  • Microsoft SQL Server
  • Microsoft Azure
  • Microsoft Excel

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