Roles › Chief Executive Officer › Chief Data (& Analytics) Officer › Data Science & ML › Data Scientists

Data Science & ML

What does a Data Scientist do?

Explore data, build models, test hypotheses.

High demand Team: Data Scientists Reports into: Data Science & ML

What they actually do

Frame business problems as prediction or inference problems.
Engineer features, train and evaluate models.
Advanced analyses: causal inference, forecasting, segmentation.
Prototype in notebooks, hand to ML engineers.

Hiring demand

High demand. Large, steady volume of postings across industries. A realistic target for an active job search.

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Who they work with

AnalystsML engineersProduct managers

Typical tools

Python (pandas, scikit-learn)JupyterSQL

Skills to get there

Statistics
Machine learning
Python
SQL

Title ladder

Common titles for this role at each level. Companies vary; see Role titles decoded.

Level	Typical titles
Entry	Junior / Associate Data Scientist · Data Scientist I
Mid	Data Scientist · Data Scientist II
Senior	Senior Data Scientist · Lead Data Scientist
Expert (IC track)	Staff / Principal Data Scientist
Management track	Manager, Data Scientists → Director of Data Scientists → VP

See the free training path →

See current openings

Searching for: Data Scientist · anywhere in the US · change

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Opens the job board's own search; results and counts are theirs.

How to get here

Salary (US) as of 2026-11

Median$120K

Typical range$85K–$181K

Senior / manager$232K

Sources:

Mapped to BLS 15-2051. Levels.fyi skews to big tech and includes equity; Payscale skews to smaller employers. Senior figure is Glassdoor's Data Science Manager median.

Experience to get here

Entry level0-2 years

Typical title2-6 years

Bachelor's minimum; master's or PhD common. 2026 posting analysis: 24% require PhD, 30% master's, 20% bachelor's, 26% unspecified. Stats, CS, math, economics are typical majors.

Typical prior roles

Data AnalystSenior Data AnalystAnalytics EngineerAcademic researcher / PhDData Science intern

Must have

Python (pandas, scikit-learn) at a fluent level (named in ~57% of postings)
Machine learning fundamentals: feature engineering, validation, evaluation (named in ~69% of postings)
SQL on a cloud warehouse (named in ~30% of postings)
Statistics: inference, regression, experiment design and A/B testing
Communicating model results and uncertainty to non-technical stakeholders

Milestones people hit first

Built and evaluated a predictive model end to end on real business data, then wrote it up
Designed and analyzed an A/B test or quasi-experiment that changed a decision
Handed a notebook prototype to engineering and saw it reach production
Owned a metric definition or forecasting process used by leadership

Certifications

AWS Certified Machine Learning Engineer - AssociateAmazon Web Services

Preferredin postings: sometimes

Exam fee	$150
Training	AWS Skill Builder free tier; paid prep courses optional
Renewal	recertify by exam every 3 years
Typical total	$150-400

Time: 6-10 weeks part-time
Prerequisites: none; AWS recommends ~1 year with SageMaker/AWS

AWS appears in ~20% of DS postings (365 Data Science, 2026); the retired ML Specialty's successor.

Google Cloud Professional Machine Learning EngineerGoogle Cloud

Nice to havein postings: sometimes

Exam fee	$200
Training	Google Skills learning path; free and paid options
Renewal	valid 2 years; renew via Google Skills courses
Typical total	$200-500

Time: 6-10 weeks part-time
Prerequisites: none; 3+ years industry and 1+ year GCP recommended

Shows up in postings at GCP-based companies; Google Cloud named in ~4% of DS postings.

Databricks Certified Machine Learning AssociateDatabricks

Nice to havein postings: rarely

Exam fee	$200
Training	Databricks Academy self-paced courses
Renewal	valid 2 years; retake current exam
Typical total	$200-400

Time: 4-6 weeks part-time
Prerequisites: none; ~6 months hands-on recommended

Useful where the company runs on Databricks/Spark; rarely named in generic DS postings.

Google Advanced Data Analytics Professional CertificateGoogle / Coursera

Nice to havein postings: rarely

Exam fee	not published
Training	$49/mo Coursera; most finish under $300; financial aid available
Renewal	$0
Typical total	under $300

Time: about 6 months at 10 hrs/week
Prerequisites: none

Covers Python, regression and ML basics for analysts moving toward junior DS; not a hiring requirement.

Training & learning

Machine Learning Specialization (Andrew Ng) FREE Stanford Online / DeepLearning.AI on Coursera · course · free to audit; $49/mo for certificate · about 95 hours (2 months at 10 hrs/week)The standard first ML course; regression, classification, trees, clustering, evaluation in Python.
Deep Learning Specialization DeepLearning.AI on Coursera · course · Coursera subscription ($49/mo or Coursera Plus $239/yr); financial aid available · about 3 months at 10 hrs/weekDeep learning named in ~12% of DS postings and 56% of ML engineering postings; this is the common next step.
DeepLearning.AI short courses (RAG, agents, evals) FREE DeepLearning.AI · learning path · short courses free; specializations paid via Coursera · 1-2 hours eachNLP/LLM skills rose from ~5% to ~19% of DS postings; short courses cover RAG and agent patterns quickly.
The Data Scientist Job Market in 2026 (827 postings analyzed) FREE 365 Data Science · community · free · 30 minutesShows which skills, degrees and salary bands actually appear in postings, so you can prioritize study.
Online Master of Science in Analytics or Data Science (part-time) various universities · degree · varies widely; some employers fund · 1-3 years part-time74% of data scientists in a 1,001-profile study held a master's or PhD; a degree is the most common bridge from analyst.

Sources & notes

Certification frequency: 365 Data Science found AWS named in 19.7% of DS postings and Google Cloud in 3.9%, but no cert is 'often' required; most postings list none. AWS ML Specialty was retired March 31, 2026 and the TensorFlow Developer Certificate exam is closed, so both are omitted. The 1,001-profile education study is from 2019. Prior-role shares come from that study (13% data analyst, 42% already DS). Free training is limited to Coursera-audit and DeepLearning.AI short courses; Kaggle/fast.ai are not listed.

Figures are US, from the sources listed, and change often; verify before deciding.

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