$60k - $120k
relevant to our organization Experience in managing large-scale data and utilizing parallel I/O libraries (HDF5, ADIOS, NetCDF)... ...large-scale datasets Work closely with interdisciplinary teams— scientists, data analy…
Engineering & IT · Albuquerque, NM
Data Scientist jobs in Albuquerque, NM
Data scientists turn raw data into decisions and products, using statistics, experimentation, and machine learning to answer questions the business could not otherwise settle.
144
Open roles today
$36–$89/hr
Typical pay range
$121k
Median, full-time
4
Fresh in this list
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01
Open data scientist roles
12 shown of 144 · sorted by freshness
Key Responsibilities Data Pipelines & Platforms Lead pipeline architecture decisions for assigned workstreams, including batch and real-time ingestion, transformation, and delivery to analytics and AI layers. Design, bui…
your expertise, you might design infrastructure in remote locations, develop renewable energy solutions for global projects, or apply data- driven technology to improve mining and water systems. We bring deep technical k…
$54k
Salary: $54,000 - 54,000 per year Requirements: We are looking for 2+ years of experience in a corporate IT or managed services environment; MSP or multi-client experience is a strong advantage. We need someone who is co…
$95.5 per hour
JOB TITLE: Electrophysics Engineer/ Scientist 4 LOCATION: Albuquerque, NM PAY RATE: $95.50/hour We are a national aerospace... ...in Electrical, Mechanical or Aeronautical, Computer Science, Data Science, Mathematics, Ph…
your expertise, you might design infrastructure in remote locations, develop renewable energy solutions for global projects, or apply data- driven technology to improve mining and water systems. We bring deep technical k…
your expertise, you might design infrastructure in remote locations, develop renewable energy solutions for global projects, or apply data- driven technology to improve mining and water systems. We bring deep technical k…
is a trusted leader in complex technology domains, delivering data- driven solutions in aerospace, biosecurity, and defense. We specialize... ...Job Description BryceTech is seeking an Engineer / Scientist to provide sci…
is a trusted leader in complex technology domains, delivering data- driven solutions in aerospace, biosecurity, and defense. We specialize... ...Job Description BryceTech is seeking a Senior Engineer/ Scientist to provid…
is a trusted leader in complex technology domains, delivering data- driven solutions in aerospace, biosecurity, and defense. We specialize... ...BryceTech is seeking a highly experienced Principal Engineer/ Scientist to…
$130k - $180k
, firewalls, network segmentation, and secure remote connectivity • Experience integrating Azure environments with on-premises data centers, Active Directory, enterprise networks, and remote operating locations • Experie…
$120k - $130k
identify and solve a variety of problems and to clarify management objectives. ~ Present the results of mathematical modeling and data analysis to management or other end users. ~ Collaborate with others in the organizat…
02
What data scientists earn in Albuquerque
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $36–$49 | $74k–$102k |
| Mid level | $49–$67 | $102k–$140k |
| Senior | $65–$89 | $135k–$186k |
Adjusted for the Albuquerque market from national ranges.
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What employers ask for
The skills these listings keep naming
Python (pandas, scikit-learn)SQLStatistics and A/B testingMachine learning fundamentalsData visualizationExperiment designCommunicating with stakeholdersDomain and product sense
04
Interview questions worth rehearsing
With the thing the interviewer is actually listening for
Walk me through a data project that changed a decision.
Structure it as question, approach, finding, action. Projects that ended in a decision — even 'we did not launch' — beat technically impressive analyses that went nowhere.
How would you design an A/B test for a new feature?
Cover the metric, randomization unit, sample size, and duration, plus a pitfall like peeking or interference. Practical rigor is what is being tested.
Your model performs well offline but poorly in production. Why might that be?
Discuss train/serve skew, data leakage, distribution shift, and feedback loops. Listing several plausible causes and how you would check each is the strong answer.
Explain p-values or confidence intervals to a non-technical stakeholder.
Use plain language and a concrete scenario, and resist overstating certainty. They are testing whether your statistics survive translation.
How do you handle missing or messy data?
First ask why it is missing — the mechanism matters more than the imputation method. Then discuss options and how the choice affects conclusions.
When would you not use machine learning for a problem?
When a rule, a query, or a simple heuristic wins on cost and interpretability. Knowing when ML is overkill signals maturity.
How do you decide which metric a team should optimize?
Talk about proxy versus true goals, gameability, and counter-metrics. A story about a metric that backfired is very effective here.
05
Resume tips that move the needle
For data scientists specifically — generic advice costs you here
01
Lead every bullet with the business result — revenue, retention, cost — and put the method second.
02
Specify your stack concretely: Python libraries, SQL dialects, experimentation platforms, and any production ML experience.
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Distinguish shipped work from research; 'model serving 2M users' and 'notebook analysis' are different claims.
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Keep one or two public projects or publications linkable, tailored to the industry you are targeting.
05
Name the size and kind of data you worked with — event streams, tabular, text — so teams can map you to their problems.
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Where this role goes
Typical progression
01
Junior Data Scientist
02
Data Scientist
03
Senior Data Scientist
04
Staff Data Scientist
05
Head of Data Science
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