UPSPosted 11mo ago

Applications Developer – Data Analyst, Data Science, Python, GCP, ML

Applications Developer – Data Analyst, Data Science, Python, GCP, ML at UPS scores 85 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

IN - TDC 1 (IN110)seniorFull time

AI in this role

computer-visionnlp

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Job Description:

Job Title: Data Analyst – DSML Team

Overview
We are looking for a Data Analyst to support the DSML team in advancing projects across computer vision, NLP, and LLM applications. The ideal candidate will be hands-on with data, detail-oriented, and comfortable working across data engineering and machine learning workflows.

Key Responsibilities

Support the DSML team by labeling objects in computer vision projects.
Review and evaluate retrieval quality for LLM and NLP projects.
Assist in data engineering tasks, including data preparation, transformation, and validation.
Help tune model parameters and contribute to improving model performance.
Collaborate with cross-functional teams to ensure data quality and project success.

Required Skills & Experience

Programming: Python, Pandas, SQL, Flask, Web Services.
Skills: Data Engineering, Machine Learning, Deep Learning, Computer Vision.
Tools: Google Cloud Platform (GCP), hands-on experience with Large Language Models (LLMs).
Strong analytical and problem-solving skills with attention to detail.
Ability to communicate findings and collaborate effectively with technical and non-technical stakeholders.

Qualifications
• Min 5 to 7 years of experience
• Bachelor’s Degree or International equivalent

Employee Type:

Permanent

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Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Computer VisionNlp

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
What NLP problem have you worked on, and how did you measure whether it actually worked?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: Computer Vision and Nlp. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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