RoleMath

role

Computer and Information Research Scientists

Source-cited RoleMath page about Computer and Information Research Scientists.

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Researched by RoleMath Research. Every figure on this page traces to the official source shown next to it.

What the numbers say about this work

Government occupation data for the role this maps to — Computer and Information Research Scientists (SOC 15-1221). This is planning context for the occupation, not a salary or a job this role guarantees you.

Median pay (occupation)
$140,300 / yr · $82,200 to $230,630 (10th–90th percentile)
Projected change (2024–34)
+19.7% · ~3.2k openings/yr
Typical entry education
Master's degree

BLS OEWS — occupation-level, national BLS Employment Projections 2024–34 This role has a high-confidence mapping to the listed O*NET-SOC/BLS occupation.

What it pays by metro

The national median hides a wide geographic spread. Below is the occupation’s median in some of the highest-paying and largest-employment metros, adjusted for local prices — regional price-level context, not take-home pay or a salary this role guarantees you.

MetroNominal medianCost-adjusted
San Jose, CA$218,420$197,803
Seattle, WA$211,270$190,106
Boston, MA$170,510$157,492
New York, NY$170,890$151,817
Baltimore, MD$156,750$150,019
San Francisco, CA$171,440$148,288

See all metros and how this is calculated → Sources: BLS OEWS (May 2025), occupation-level metro median ÷ BEA Regional Price Parities (2024, US=100).

What this work involves

The tasks the U.S. Department of Labor’s O*NET lists most central to this occupation — role-fit evidence to weigh against your background, not a measure of employer demand.

  • Analyze problems to develop solutions involving computer hardware and software.
  • Apply theoretical expertise and innovation to create or apply new technology, such as adapting principles for applying computers to new uses.
  • Assign or schedule tasks to meet work priorities and goals.
  • Meet with managers, vendors, and others to solicit cooperation and resolve problems.
  • Design computers and the software that runs them.
  • Conduct logical analyses of business, scientific, engineering, and other technical problems, formulating mathematical models of problems for solution by computers.

O*NET — occupation-level

Skills that matter

The skills O*NET rates most important for this occupation. A starting map for what to build — weigh it against the specific job you’re targeting.

  • Critical Thinking
  • Active Listening
  • Reading Comprehension
  • Active Learning
  • Speaking
  • Mathematics
  • Writing
  • Monitoring

O*NET — occupation-level

Certification decision support

Certifications mapped to Computer and Information Research Scientists

Certifications mapped to this role from cited OEM target-role data and the RoleMath role mapping, ordered by relationship strength and then Difficulty Score. This is planning context — not a guarantee, not an employer requirement, and not a claim that any one certification is best for everyone. Your fit depends on your background; pay/outlook context is occupation-level on the role page.

Start here signalAWS Certified Machine Learning Engineer - Associate60/100 · Hard

Advanced or later-step credentials

6 mapped

Credentials that may matter after experience builds; they are not presented as first steps.

CredentialDifficultyCostRelationshipWhy it appears here
AWS Certified Machine Learning Engineer - AssociateAmazon Web Services · Associate
60/100Hard$150 examadvanced adjacentAWS Certified Machine Learning Engineer - Associate maps to Computer and Information Research Scientists as an advanced credential for progressing toward/within this role, not an entry signal.Official source
Oracle Cloud Infrastructure Certified Data Science ProfessionalOracle · professional
60/100HardCost not verifiedadvanced adjacentOracle Cloud Infrastructure Certified Data Science Professional maps to Computer and Information Research Scientists as an advanced credential for progressing toward/within this role, not an entry signal.Official source
Databricks Certified Machine Learning ProfessionalDatabricks · professional
70/100Hard$200 examadvanced adjacentDatabricks Certified Machine Learning Professional maps to Computer and Information Research Scientists as an advanced credential for progressing toward/within this role, not an entry signal.Official source
Professional Data EngineerGoogle Cloud · professional
75/100Hard$200 examadvanced adjacentProfessional Data Engineer maps to Computer and Information Research Scientists as an advanced credential for progressing toward/within this role, not an entry signal.Official source
Professional Machine Learning EngineerGoogle Cloud · professional
75/100Hard$200 examadvanced adjacentProfessional Machine Learning Engineer maps to Computer and Information Research Scientists as an advanced credential for progressing toward/within this role, not an entry signal.Official source
SnowPro Advanced: Data ScientistSnowflake · professional
80/100Expert$375 examspecializedSnowPro Advanced: Data Scientist maps to Computer and Information Research Scientists as an advanced credential for progressing toward/within this role, not an entry signal.Official source

Difficulty is the RoleMath Difficulty Score, not a pass rate. Certification mappings are planning context, not employer requirements, job guarantees, salary claims, or ROI claims.

Answer blocks

Common Questions

What certifications do I need to become a Computer and Information Research Scientists?

RoleMath does not currently map an entry-level certification to a Computer and Information Research Scientists role. The cited credentials in this lane are advanced or later-step credentials such as AWS Certified Machine Learning Engineer - Associate, Oracle Cloud Infrastructure Certified Data Science Professional, Databricks Certified Machine Learning Professional. Treat them as specialization signals, not beginner starting points.

Advanced or later-step credentials: AWS Certified Machine Learning Engineer - Associate (Amazon Web Services; Difficulty Score 60/100, Hard; exam ~$150); Oracle Cloud Infrastructure Certified Data Science Professional (Oracle; Difficulty Score 60/100, Hard; exam fee pending vendor verification); Databricks Certified Machine Learning Professional (Databricks; Difficulty Score 70/100, Hard; exam ~$200).

Citations: Source rows are visible in the page citation ledger; certification source URLs are linked in the decision table.

Use the RoleMath planner to adapt this sequence to your background, budget, and timeline. RoleMath sells nothing.

How much do Computer and Information Research Scientists certifications cost and how hard are they?

Cited Computer and Information Research Scientists certification exam fees range roughly $150–$375, spanning around Hard later-step credentials on the RoleMath Difficulty Score. Pay and outlook are reported at the occupation level on the Computer and Information Research Scientists page, never per certification.

Advanced or later-step credentials: AWS Certified Machine Learning Engineer - Associate (Amazon Web Services; Difficulty Score 60/100, Hard; exam ~$150); Oracle Cloud Infrastructure Certified Data Science Professional (Oracle; Difficulty Score 60/100, Hard; exam fee pending vendor verification); Databricks Certified Machine Learning Professional (Databricks; Difficulty Score 70/100, Hard; exam ~$200).

Citations: Source rows are visible in the page citation ledger; certification source URLs are linked in the decision table.

Use the RoleMath planner to adapt this sequence to your background, budget, and timeline. RoleMath sells nothing.

Computer and Information Research Scientists

Quick Verdict

Computer and Information Research Scientists maps to the BLS occupation Computer and Information Research Scientists (SOC 15-1221), which has a national median of $140,300. Pay is occupation-level and location-driven - not caused by the job title or a certification. Below are the full cited labor-market context, the skills the role draws on, and the certification paths that map to it. This role has a high-confidence mapping to the listed O*NET-SOC/BLS occupation.

Fit Signals

  • Investigative (7)
  • Conventional (4.8)
  • Realistic (3.74)

Skills & Tools

*Tools and technologies ONET associates with this occupation* - role-specific examples with ONET hot/in-demand flags, not employer requirements:

  • Amazon Web Services AWS software (hot technology, in demand)
  • Ansible software (hot technology, in demand)
  • Apache Hadoop (hot technology, in demand)
  • Apache Kafka (hot technology, in demand)
  • Apache Spark (hot technology, in demand)
  • Bash (hot technology, in demand)
  • C (hot technology, in demand)
  • C++ (hot technology, in demand)

*Foundational ONET skills** (broadly shared across occupations, not unique to this role): Critical Thinking, Active Listening, Reading Comprehension, Active Learning, Speaking, Mathematics.

AI & this career

What we can — and can’t — tell you about AI and this role

Cited context only: an occupation-level outlook, descriptive usage data, an employer-language sample, and attributed research — kept separate. No RoleMath AI score, no automation timeline, no job-loss prediction. How we source this →

Occupation outlook · BLS

Where the occupation is projected to go

BLS projects Computer and information research scientists at 19.7% employment change for 2024-2034, with 3.2 thousand annual openings. U.S. Bureau of Labor Statistics

A forecast, not a guarantee; occupation-level, not about you - and BLS does not model rapid AI adoption, so this is never an AI prediction.

How AI shows up in the work

Descriptive usage, not demand or loss

For this shared SOC, the May 2026 usage sample reports 42.07% augmentation-labeled and 57.93% automation-labeled Claude conversations. Anthropic Anthropic Economic Index dataset, CC-BY.

Across all occupations the same dataset splits 51.4% augmentation / 48.6% automation (May 2026) — shown so a single role’s number is never read as an outlier.

Descriptive Claude usage data, not employment demand, not job loss, and not a personal forecast; CC-BY attribution required.

Employer language · sample

What a posting sample mentions

not yet in the posting sample.

Published research · attributed

What independent research says (not RoleMath’s claim)

  • Eloundou et al. estimate that about 80% of U.S. workers have at least 10% of their work tasks exposed to large language model capabilities (Science 2024). American Association for the Advancement of Science exposure = task overlap, not job loss.
  • Eloundou et al. estimate that about 19% of U.S. workers have at least 50% of their work tasks exposed to large language model capabilities (Science 2024). American Association for the Advancement of Science exposure = task overlap, not job loss.
  • Eloundou et al. explicitly disclaim any forecast of AI adoption or timing, describing their measure as capability overlap with tasks rather than a prediction of job loss (Science 2024). American Association for the Advancement of Science exposure = task overlap, not job loss.
  • OECD reports that high-skill occupations are the most exposed to AI on task-overlap measures (OECD Employment Outlook 2023). Organisation for Economic Co-operation and Development exposure = task overlap, not job loss.
  • OECD reports that, as of 2023, there is little empirical evidence of negative employment effects from AI (OECD Employment Outlook 2023). Organisation for Economic Co-operation and Development exposure = task overlap, not job loss.
  • OECD and the AIOE research find that AI exposure and automation risk often run in opposite directions, with the most-exposed high-skill occupations tending to be the least at risk of automation. Organisation for Economic Co-operation and Development exposure = task overlap, not job loss.
  • Felten, Raj and Seamans construct an occupation-level AI Occupational Exposure index by linking AI capabilities to O*NET occupational abilities (Strategic Management Journal). Strategic Management Journal (Wiley) exposure = task overlap, not job loss.
  • Stanford Digital Economy Lab researchers find a roughly 16% relative decline in employment for workers ages 22-25 in the most AI-exposed occupations, based on high-frequency ADP payroll data (Canaries in the Coal Mine, working paper). Stanford Digital Economy Lab correlational usage data, not proof.
  • The ILO notes that AI-exposure indicators measure potential task overlap and cannot by themselves establish job loss (Workers' exposure to AI). International Labour Organization exposure = task overlap, not job loss.
  • The Anthropic Economic Index reports no measured systematic rise in unemployment attributable to AI in its usage data. Anthropic correlational usage data, not proof.

Tier A research stays attributed and separate from BLS outlook and employer-language samples.

Every page here connects to the same cited data spine — these are the closest surfaces to what you just read.

Roles & paths this connects to

role role interestWhat interests fit a Computer and Information Research Scientists?role role learning roadmapLearning roadmap: how to become a Computer and Information Research Scientistsrole role outlookJob outlook & openings: Computer and Information Research Scientists

Zoom out

relevant learning programClaude 101relevant learning programAI Fluency: Framework & Foundationsrelevant learning programAnthropic Academy

Every figure on this page, sourced

The claims above trace to these records — the source, and when it was last checked. If a figure has no row here, we did not publish it.

IDSupportsSourceChecked
SCHEMA-CIT-1Schema citationComputer and Information Research Scientists BLS OEWS wage sourceLogged in source packet
SCHEMA-CIT-2Schema citationComputer and Information Research Scientists BLS Employment Projections sourceLogged in source packet
SCHEMA-CIT-3Schema citationComputer and Information Research Scientists O*NET sourceLogged in source packet

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