Senior Analytics Engineer
Listed on 2026-03-09
-
IT/Tech
Data Science Manager, Data Analyst
Date Posted:
Country: United States of America
Location: HCT
99:
Field Office - CT Remote Location, Remote City, CT, 06101 USA
Position Role Type: Remote
U.S. Citizen, U.S. Person, or Immigration Status Requirements: U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract.
Security Clearance Type: None/Not Required
Security Clearance Status: Not Required
We are seeking a Senior Analytics Engineer to join our Product Lifecycle Analytics team, supporting cutting‑edge electro‑mechanical systems operating around the world. In this role, you will leverage your deep engineering expertise and strong statistical foundation to help develop and mature an end‑to‑end digital thread across a portfolio of Collins Aerospace products.
As a senior member of the team, you will play a critical role in integrating data across historically siloed business units, transforming complex engineering and operational data into actionable insights. Your work will directly influence product performance, service optimization, and enterprise business intelligence strategies.
This position requires a strategic thinker who can bridge engineering knowledge with advanced analytics, drive cross‑functional collaboration, and lead initiatives that elevate data‑driven decision‑making across the organization.
What You Will Do- Develop a strong understanding of core electrical and mechanical system principles
- Conduct data analysis with Python to drive informed business decisions
- Apply statistical methods to assess data completeness, accuracy, and reliability
- Support engineering teams with root cause analysis investigations
- Promote the adoption of semantic models and ontologies across the organization
- Design and build executable Python‑based analytical models
- Automate data processing, analysis, and formatting workflows
- Clean, structure, and analyze datasets using Python
- Organize data and implement standardized labeling practices in AWS S3
- Deploy machine learning algorithms on both numerical and categorical data sets
- Typically requires a degree in Science, Technology, Engineering or Mathematics (STEM) and minimum 5 years prior relevant experience or an Advanced Degree in a related field and minimum 3 years of experience
- Background in Data Science, Statistics, or an Engineering discipline
- Proficiency in Python for data analysis and model development
- Experience with in the Aerospace & Defense industry or Information Systems environments
- Familiarity with graph databases, semantic layers, and data ontology frameworks
- Hands‑on experience with cloud and distributed technologies such as AWS, Azure, or Apache Spark
- Knowledge of Git or similar version control systems, following software development best practices
- Understanding of the full software development lifecycle, from concept through deployment
- Experience using Agile collaboration and project management tools such as Jira and Confluence
Some of our competitive benefits package includes:
- Medical, dental, and vision insurance
- Three weeks of vacation for newly hired employees
- Generous 401(k) plan that includes employer matching funds and separate employer retirement contribution, including a Lifetime Income Strategy option
- Tuition reimbursement program
- Student Loan Repayment Program
- Life insurance and disability coverage
- Optional coverages you can buy pet insurance, home and auto insurance, additional life and accident insurance, critical illness insurance, group legal, protection
- Birth, adoption, parental leave benefits
- Ovia Health, fertility, and family planning
- Adoption Assistance
- Autism Benefit
- Employee Assistance Plan, including up to 10 free counseling sessions
- Healthy You Incentives, wellness rewards program
- Doctor on Demand, virtual doctor visits
- Bright Horizons, child and elder care services
- Teladoc Medical Experts, second opinion program
- And more!
Employees who are working in Remote roles will work primarily offsite (from home). An employee may be expected to travel to the site location as needed.
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