Data Science Intern, Asset Intelligence

PerkinElmer

. Trace asset records from raw customer intake through normalization, classification, and enrichment .

Posted 9/15/2026part-timeRemote • New York • United StatesEntry Level💰 $25 - $40 per hourWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Proficient in data cleaning, record matching, and classification, with strong skills in Python and SQL. Capable of analyzing data attributes and maintaining documentation for reproducibility in a remote work environment.

Highest-signal resume keywords

Python ProgrammingSQL Database ManagementData CleaningRecord MatchingPandas Library

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data CleaningRecord MatchingClassificationData AnalysisPython ProgrammingSQL Database ManagementAI-Assisted Text ProcessingData DeduplicationJupyter NotebookStatistical Analysis

Soft Skills

Clear Written CommunicationSelf-MotivationRemote Work Adaptability

Tools & Technologies

PandasJupyterData Repositories

Industry Keywords

Scientific InstrumentationLaboratory Operations

Tech Stack

Tools & technologies

PandasPythonSQL

About the role

Key responsibilities & impact

Trace asset records from raw customer intake through normalization, classification, and enrichment
Reproduce the production pipeline on sample data and confirm matching results
Document service judgment calls, evidence used, and fragile decisions
Build and maintain a gold-standard reference set of correctly classified instruments
Score match rate and classification accuracy by equipment class
Re-score after every change to demonstrate improvement
Cluster near-duplicate records and reconcile them with their alias sets
Improve classifier input text by separating technical capability language from application and use-case language
Analyze attribute coverage across the record base field by field
Maintain code and queries in the team repository
Write method notes alongside code for repeatable handoff
Perform ad hoc data pulls and analysis for the team

Requirements

What you’ll need

Currently enrolled in a bachelor's degree program in data science, statistics, computer science, or a related field
Working knowledge of Python and SQL
Available approximately ten hours per week during the academic term
Coursework or project experience in data cleaning, record matching, deduplication, or classification
Familiarity with pandas and Jupyter, or the equivalent in R
Some exposure to AI-assisted text processing, along with the instinct to verify what it returns rather than accept it
Comfortable working remotely from written direction with limited supervision
Clear written communication
Interest in scientific instrumentation or laboratory operations; no prior domain knowledge is required

Benefits

Comp & perks

Hourly compensation of $25–$40 per hour
Part-time schedule of approximately ten hours per week during the academic term
Remote work arrangement