What are the responsibilities and job description for the Junior Operations Analyst position at Implementation Engineers?
Junior Operations Analyst
Location: remote (60-75% client-site travel) | Full Time
At Implementation Engineers, we don’t just advise -- we implement.
You’ll work on real factory floors, solve complex problems,
and see your solutions stick in productivity, quality, and cost performance.
What you’ll do
- Dive into manufacturing operations, analyze problems, and implement fixes that move the needle.
- Build dashboards and models to turn shop-floor data into decisions (Power BI/Excel/SQL/Python).
- Collaborate with experienced engineers and client teams; document results and standardize wins.
- Travel to client sites across the U.S. to work hands-on with operations.
Who you are
- Problem-solver with strong analytical chops and a bias for action.
- Clear communicator who’s comfortable on the shop floor and with executives.
- Curious, coachable, and energized by fast-moving environments.
- Willing to travel frequently (week-to-week variability; expect significant on-site work).
Qualifications
- Education: BS/MS in Mechanical, Industrial, Manufacturing, Chemical, Computer/Software (AI/ML/Data), or related engineering field.
- Experience: 0–5 years; 1–5 years in manufacturing preferred (internships/co-ops count).
- Tools: Power BI (or Tableau), Excel, basic SQL; Python a plus (required for AI/Data track).
Choose your path (we’ll place you where you’ll thrive)
Supply Chain
- Interests/skills: material flow, PFEP, inventory optimization, planning/SIOP, logistics, line balancing.
- Familiarity with ERP/MRP (SAP/Oracle/other) and shop-floor data.
- Deliverables: value stream maps, PFEP builds, inventory and throughput models, line-side kit/route designs.
Maintenance & Asset Performance Engineering (APE)
- Interests/skills: RCA/5 Whys/FMEA, reliability basics, TPM, PdM/CBM, CMMS exposure.
- Comfort with time-series data from sensors; translating findings into maintenance plans.
- Deliverables: PM/PdM routes, failure analyses, loss trees, criticality rankings, uptime/MTBF improvements.
AI / Data Science for Industry 4.0
- Skills: Python, data wrangling, time-series/ML basics; bonus for LLM/RAG/OpenAI API experience.
- Comfort building small data pipelines and lightweight models tied to shop-floor outcomes.
- Deliverables: clean datasets, diagnostic models, copilots/assistants, and BI integrations that operators actually use.
Nice-to-haves (any track)
- Lean/CI exposure (5S, Kaizen, standard work), SPC/statistics, simulation, basic scripting.
- Power BI DAX, SQL joins/windows, Git, Jupyter; vibration/IR/ultrasound basics.
- Strong presentation skills; turning analyses into crisp operator playbooks.
What you’ll get
- Accelerated learning with senior mentors and diverse plants/industries.
- Visible impact—your work changes how factories run.
- A collaborative, no-ego culture that values curiosity and results.