What it pays
Government survey numbers — not estimates, not ads.
Half of all Data Scientists in the U.S. earn more than $120,230 a year — the middle 80% land between $67,240 and $199,130. About 262,440 people in the U.S. do this work. Figures are for the U.S. occupation group “Data Scientists”. (U.S. Bureau of Labor Statistics survey, published 2025.) In India, Professionals earn about ₹38,298 a month on average — around ₹4.6 lakh a year (government PLFS survey via ILOSTAT, occupation-family figure).
$120,230typical pay / year
262,440people in this work
$199,130+top 10% earn
₹4.6 lakha year in India (family avg)
Think you get this job?Six quick questions on how it really works — with a hint and the reason behind every answer.
Test yourself →The work, task by task
These are the real jobs-to-be-done, not a wish list. Each task shows where we found it, and the prompt underneath is written for that exact task.
Analysing6
Manage large amounts of data
+Prepare the labeling backlog for the next quarter: prioritise high-impact datasets, estimate human-hours per…
Manage large amounts of data
+Prepare the labeling backlog for the next quarter: prioritise high-impact datasets, estimate human-hours per dataset, assign teams for image, text and RDF tasks, and publish the schedule to the project channel by Thursday so hiring can follow.
The tools that do the workAtlassian JIRAAtlassian ConfluenceESCOO*NETWikipedia
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Develop and test data models
+Run the model iteration plan: select the cleaned training partitions, run the candidate recommender model on…
Develop and test data models
+Run the model iteration plan: select the cleaned training partitions, run the candidate recommender model on the test split, capture metric changes and failure examples, then hand failing slices to the labeling team for targeted annotation by Friday.
The tools that do the workApache SparkESCOjob descriptionsWikipedia
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Present findings through reports and presentations
+Draft the monthly findings report: summarise label quality trends, model performance by cohort, annotation…
Present findings through reports and presentations
+Draft the monthly findings report: summarise label quality trends, model performance by cohort, annotation throughput and blocker incidents, include three visualisations and a one-page executive summary for Tuesday's leadership meeting.
The tools that do the workAtlassian ConfluenceESCOjob descriptionsO*NET
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Communicate insights to stakeholders
+Prepare stakeholder briefs: create a two-slide summary of risks and recommended actions from the latest label…
Communicate insights to stakeholders
+Prepare stakeholder briefs: create a two-slide summary of risks and recommended actions from the latest label audit, list required decisions from procurement and product by Wednesday, and request a 30-minute review slot with Priya and Marcus.
The tools that do the workAtlassian ConfluenceESCOjob descriptionsO*NET
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Apply machine learning techniques
+Prototype the ML feature pipeline: select cleansed label sets, engineer candidate features for the…
Apply machine learning techniques
+Prototype the ML feature pipeline: select cleansed label sets, engineer candidate features for the recommender, run cross-validation to measure lift, and record feature importance and failure cases for the engineers by end of week.
The tools that do the workApache Sparkjob descriptionsO*NET
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Merge data sources
+Consolidate the data sources for the master label store: map fields from the CRM export, web logs and legacy…
Merge data sources
+Consolidate the data sources for the master label store: map fields from the CRM export, web logs and legacy RDF dump, deduplicate by customer ID, validate sample joins, then publish the reconciled file for annotation by Monday.
The tools that do the workApache HiveESCOjob descriptions
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The daily work17
Identify business problems and data solutions
+Identify the top three business problems that poor labels are causing in our recommender pipeline, map each…
Identify business problems and data solutions
+Identify the top three business problems that poor labels are causing in our recommender pipeline, map each problem to a concrete data solution we can staff and budget this quarter, and produce a one-page brief for Priya in product and Mark in engineering by Thursday.
The tools that do the workAtlassian JIRAAtlassian Confluencejob descriptionsO*NET
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Analyze data to identify patterns and trends
+Run an analysis to surface recurring labeling errors and behavioural patterns across the last three months of…
Analyze data to identify patterns and trends
+Run an analysis to surface recurring labeling errors and behavioural patterns across the last three months of annotation work, quantify error rates by labeler team and data slice, and deliver a slide with findings and recommended fixes to send to the annotation managers on Monday.
The tools that do the workApache Sparkjob descriptionsO*NET
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Categorize and organize data
+Create a clean taxonomy for our image and text labels, collapse redundant tags, propose authoritative parent…
Categorize and organize data
+Create a clean taxonomy for our image and text labels, collapse redundant tags, propose authoritative parent categories, and publish the updated category list with examples for the annotation team before the next sprint planning on Wednesday.
The tools that do the workApache Hivejob descriptionsWikipedia
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Create data visualizations and dashboards
+Build a dashboard showing label distribution, inter-annotator agreement, and model performance by label for…
Create data visualizations and dashboards
+Build a dashboard showing label distribution, inter-annotator agreement, and model performance by label for the last 90 days, add filters for data slice and labeler, and share the dashboard link with the product leads ahead of Friday's review.
The tools that do the workApache KafkaESCOjob descriptions
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Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
+Design and document a sampling plan that specifies when to use stratified sampling versus full enumeration…
Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
+Design and document a sampling plan that specifies when to use stratified sampling versus full enumeration for our ICT data audits, include sample sizes, confidence levels, and the impact on labeling workload, and circulate it to quality and ops by Tuesday.
The tools that do the workAlteryxO*NET
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Design surveys, opinion polls, or other instruments to collect data.
+Draft two survey instruments to collect annotator feedback: one quick pulse for daily usability issues and…
Design surveys, opinion polls, or other instruments to collect data.
+Draft two survey instruments to collect annotator feedback: one quick pulse for daily usability issues and one detailed form for quarterly process improvements, include question rationale and target audiences, and hand both to HR and operations by next Monday.
The tools that do the workAtlassian ConfluenceO*NET
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Read scientific articles, conference papers, or other sources of research to identify emerging analytic trends and technologies.
+Scan the latest journal articles and conference proceedings this week to extract emerging analytic methods…
Read scientific articles, conference papers, or other sources of research to identify emerging analytic trends and technologies.
+Scan the latest journal articles and conference proceedings this week to extract emerging analytic methods and technologies, note citations, flag three trends with evidence, and draft a one-page briefing for the ML team by Friday.
The tools that do the workApache SparkO*NET
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Determine available and useful data for projects
+Inventory our available internal and public datasets, assess schema quality and licensing, mark which tables…
Determine available and useful data for projects
+Inventory our available internal and public datasets, assess schema quality and licensing, mark which tables support recommender features, and produce a ranked list of usable sources with missing-field notes by Wednesday.
The tools that do the workAmazon Redshiftjob descriptions
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Clean and process raw data
+Take the raw logs and survey dumps from the last quarter, standardise dates and IDs, remove duplicates and…
Clean and process raw data
+Take the raw logs and survey dumps from the last quarter, standardise dates and IDs, remove duplicates and PII, impute missing values with documented rules, and output a cleaned dataset ready for labeling by Tuesday.
The tools that do the workAlteryxjob descriptions
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Interpret data analysis results
+Review the latest model evaluation outputs, map metric changes to data slices and label quality, write plain…
Interpret data analysis results
+Review the latest model evaluation outputs, map metric changes to data slices and label quality, write plain explanations of causes and recommended next steps for product and engineering, and circulate to stakeholders by Thursday.
The tools that do the workApache Hivejob descriptions
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Monitor and improve model performance
+Monitor model predictions and feedback streams daily, set alerts for precision or recall drift, run…
Monitor and improve model performance
+Monitor model predictions and feedback streams daily, set alerts for precision or recall drift, run root-cause checks on flagged incidents, and propose two remediation actions for the next sprint planning meeting.
The tools that do the workApache Kafkajob descriptions
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Collaborate with cross-functional teams
+Organise a cross-functional review: invite Product, Engineering, and QA, prepare a dataset readiness summary,…
Collaborate with cross-functional teams
+Organise a cross-functional review: invite Product, Engineering, and QA, prepare a dataset readiness summary, list labelling constraints and trade-offs, and decide ownership of the top three actions in that meeting on Tuesday.
The tools that do the workAtlassian JIRAAtlassian Confluencejob descriptions
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Combine statistical knowledge with coding
+Combine the labeled training set with the user interaction logs, run statistical feature selection and a…
Combine statistical knowledge with coding
+Combine the labeled training set with the user interaction logs, run statistical feature selection and a reproducible script to output candidate features and their importances, then hand off the vetted feature list for prototype recommender training by Friday.
The tools that do the workApache SparkApache HiveWikipedia
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Visualize data to identify patterns
+Produce a visual dashboard that maps label distribution, class imbalance over time, and feature correlations…
Visualize data to identify patterns
+Produce a visual dashboard that maps label distribution, class imbalance over time, and feature correlations so we can spot annotation drift and inform relabeling before the next sprint demo on Wednesday.
The tools that do the workAlteryxWikipedia
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Find and interpret rich data sources
+Search internal repositories and public ICT datasets, extract high-signal candidate tables, profile their…
Find and interpret rich data sources
+Search internal repositories and public ICT datasets, extract high-signal candidate tables, profile their schema and provenance, and summarize three actionable sources we can ingest for enrichment by next Tuesday.
The tools that do the workApache HiveApache HadoopESCO
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Ensure consistency of data-sets
+Run automated checks and a reconciliation job across labeled subsets to find inconsistent labels, flag…
Ensure consistency of data-sets
+Run automated checks and a reconciliation job across labeled subsets to find inconsistent labels, flag annotators with high disagreement, and produce a corrected consensus file plus an error report by end of day Friday.
The tools that do the workApache AirflowApache SparkESCO
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Recommend ways to apply the data
+Draft three pragmatic product use cases showing how the labeled data can improve the recommender, search…
Recommend ways to apply the data
+Draft three pragmatic product use cases showing how the labeled data can improve the recommender, search ranking, and support triage, include estimated lift, required features, and a two-sprint pilot plan for Monday's leadership review.
The tools that do the workAtlassian ConfluenceAtlassian JIRAESCO
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Built on public evidence: O*NET®, ESCO, Wikipedia, U.S. Bureau of Labor Statistics, ILOSTAT. All sources & licenses
Built on public evidence: O*NET®, ESCO, Wikipedia, U.S. Bureau of Labor Statistics, ILOSTAT. All sources & licenses