← Canon taxonomy
P1
DATA3.GEN.P1
Data Science Data Analyst
Data Science

Data Science Data Analyst

DATA3.GEN.P1

P1P1 — Entry-Level Professionalmedium0.70draftglobalv1

Represents the entry point into data science, focusing on collecting, cleaning, and interpreting data to support business needs.

Level
P1 · P1 — Entry-Level Professional · 0–2 yrs
Function · Focus
Data Science · General
Market pay (median)
Pay basis
model pending

Represents the entry point into data science, focusing on collecting, cleaning, and interpreting data to support business needs.

The story of this role

As a Data Science Data Analyst, you transform raw data into actionable insights that drive business decisions.

Who does this work

You, the Data Science Data Analyst, are tasked with understanding complex data landscapes.

The problem this role solves

  • The external problem: Your team struggles to make data-driven decisions due to unclean or poorly structured data.
  • The internal problem: You feel overwhelmed by the vast amount of data and unsure where to start in the analysis process.
  • Why it matters: Every business deserves to leverage its data effectively to make informed choices.

What the role brings

We provide tools, resources, and support to help you effectively collect, clean, and interpret data.

The plan

  1. 1. Identify business needs by collaborating with stakeholders.
  2. 2. Collect relevant data from various sources.
  3. 3. Clean and structure the data to ensure accuracy.
  4. 4. Analyze the data to uncover trends and insights.
  5. 5. Present actionable findings and recommendations to your team.

The call to action

Start utilizing best practices in data analysis today to enhance the quality of your insights.

What's at stake

Failing to effectively analyze data can lead to missed opportunities and poor decision-making for your organization.

Success looks like

You gain confidence in your analytical skills, leading to clear, data-driven recommendations that support business goals.

Summary

Represents the entry point into data science, focusing on collecting, cleaning, and interpreting data to support business needs.

Level — P1 — Entry-Level Professional

New to role or field; performs basic tasks under supervision

Scope
Own tasks within a defined component
Autonomy
Close supervision; work reviewed frequently
Complexity
Routine problems with known solutions
Impact
Own deliverables
Decision rights
Few independent decisions; escalates the rest
Leadership
None — building the craft
Typical experience
0–2 yrs

Core outputs

No core outputs recorded yet.

Adjacent roles

Nearest roles by structural coordinates (level + taxonomy). Distance 0 → 1; each carries its 3-state match band. How coordinates work → · Compare side-by-side →

Componentsshow ▾

Responsibilities8

  • Writing queries to pull datacommonlevel
  • Using tools to generate reports and simple visualizationscommonlevel
  • Summarizing trends or findings from datasetscommonlevel
  • Assisting in data cleaning and preparationcommonlevel
  • Collaborating with teams to understand data needscommonlevel
  • Supporting data-driven decision-makingcommonlevel
  • Documenting data processes and findingscommonlevel
  • Ensuring data accuracy and integritycommonlevel

Tasks3

  • Pull and analyze data setscommonlevel
  • Create visual reportscommonlevel
  • Summarize data trendscommonlevel

Skills8

  • SQL queryingcommonlevel
  • Data visualizationcommonlevel
  • Spreadsheet proficiencycommonlevel
  • Basic programming (Python/R)commonlevel
  • Data cleaningcommonlevel
  • Report generationcommonlevel
  • Trend analysiscommonlevel
  • Data interpretationcommonlevel

Knowledge8

  • Statisticscommonlevel
  • Data querying techniquescommonlevel
  • Database managementcommonlevel
  • Data visualization toolscommonlevel
  • Business intelligencecommonlevel
  • Data integrity principlescommonlevel
  • Basic programming conceptscommonlevel
  • Data-driven decision-makingcommonlevel

competency8

  • Strong foundation in statistics and data queryingcommonlevel
  • Proficiency with databases (SQL) and spreadsheet toolscommonlevel
  • Attention to detailcommonlevel
  • Analytical thinkingcommonlevel
  • Basic data visualization skillscommonlevel
  • Effective communicationcommonlevel
  • Problem-solvingcommonlevel
  • Time managementcommonlevel

qualification4

  • Ability to create clear data visualizationscommonlevel
  • Communication skillscommonlevel
  • Bachelor's degree in a related fieldcommonlevel
  • Experience with SQL and data toolscommonlevel
Title aliasesshow ▾
AliasTypeConfidenceApproved
Data Science Icommonmedium0.70
Data Science 1commonmedium0.66
Entry-Level Data Sciencecommonmedium0.70
Junior Data Sciencecommonmedium0.68
Data Science Data Analystcommonmedium0.60
Entry to Intermediate Levelcommonmedium0.50
Associate Data Sciencecommonmedium0.60
Classification mappingsshow ▾

O*NET / SOC

  • code=15-2051.00title=Data Scientistssource=corpusreviewStatus=approved