ZipRecruiter

Log In

1

Data Science Jobs in Santa Fe, NM (NOW HIRING)

HealthLeap

Principal Research Data Scientist

Santa Fe, NM · On-site

$170 - $215/hr

You'll get support from, and work closely with, our data science and engineering teams, who know the data inside and out. You might be a good fit if you're curious, care about impact, and want to do ...

HII Nuclear Inc.

Data Management Chemist

Los Alamos, NM · On-site

... sciences to understand and utilize scientific data. * Skill and ability to perform critical strategic tasks and to interpret broad strategic requirements and develop and execute plans to satisfy them.

next page

Showing results 1-20

All JobsData Science JobsData Science Jobs in Santa Fe, NM

Data Science information

See Santa Fe, NM salary details

$36.7K

$120K

$192.1K

How much do data science jobs pay per year?

As of Aug 27, 2026, the average yearly pay for data science in Santa Fe, NM is $120,017.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,300.00 and $133,000.00 per year, depending on experience, location, and employer.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

Is a data scientist in high demand?

Data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What jobs can a data scientist do?

A data scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.
More about Data Science jobs

What are the most commonly searched types of Data Science jobs in Santa Fe, NM?

The most popular types of Data Science jobs in Santa Fe, NM are:

What are popular job titles related to Data Science jobs in Santa Fe, NM?

For Data Science jobs in Santa Fe, NM, the most frequently searched job titles are:

What job categories do people searching Data Science jobs in Santa Fe, NM look for?

The top searched job categories for Data Science jobs in Santa Fe, NM are:

What cities near Santa Fe, NM are hiring for Data Science jobs?

Cities near Santa Fe, NM with the most Data Science job openings:

Data Science jobs near you
Infographic showing various Data Science job openings in Santa Fe, NM as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, 1% Temporary, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $120,484 per year, or $57.9 per hour.

Principal Research Data Scientist

HealthLeap

Santa Fe, NM • On-site

$170 - $215/hr

Other

Medical, Retirement, PTO

Re-posted 8 days ago

Job description

About Healthleap

Every day, millions of hospitalized patients who need intervention are missed because clinicians simply can't see everything. HealthLeap is building the AI operating system that helps care teams identify these missed patients, enabling them to improve health outcomes and generate millions of dollars. HealthLeap is changing what is possible: closing gaps that traditional workflows and clinician capacity could never.

Over the past year, we've grown contracted revenue more than 13x, expanded rapidly across leading health systems, and now help care teams identify patients across millions of inpatient encounters.

We're ~25 people. >$32M raised. SF-based, hybrid-friendly. And, we're delivering results that are changing lives.

About the role

At HealthLeap, you'll ask the hard questions about hospital care. Who gets missed, and for which conditions? What actually changes outcomes? Where does screening help, and where doesn\'t it? You\'ll run the statistical analyses that test whether screening every patient really changes their trajectory, look hard at the results, and figure out where we can do better. That work supports our partners and our go-to-market efforts, and it can shape a product that clinicians use every day.

You'll be early enough to build the research agenda from scratch, but late enough to know the product already works. You'll also have a lot to work with: EHR data from 40+ hospitals, hundreds of thousands of patients, real deployments, and your pick of health system partners. You’ll get support from, and work closely with, our data science and engineering teams, who know the data inside and out.

You might be a good fit if you're curious, care about impact, and want to do applied data science. It helps if you like turning messy observational hospital data into results people actually cite, and if you're excited by the speed of startups!

Where this goes

You'll be our first dedicated research hire, which means you get to help set research priorities for HealthLeap and own your research portfolio. Year one will focus on running outcomes studies and driving two studies to publication, but you will have the opportunity to shape the research team and grow with the function.

What you'll do

  • Own research projects end-to-end, from study design through analysis, interpretation, and publication.

  • Design and run observational and quasi-experimental studies on real-world hospital data.

  • Analyze complex clinical and operational datasets and stand behind the methods.

  • Collaborate with frontline clinicians, health system execs, our customer success team, our go-to-market teams, and our data science team to come up with new research questions, weigh in on product decisions, and lead the outcomes and impact studies tied to our health system partnerships.

What you'll need

  • PhD in statistics, biostatistics, epidemiology, or a related field.

  • At least 2 years of (non-PhD) experience conducting observational health research using large healthcare databases.

  • Background in epidemiology or outcomes research.

  • Deep expertise in causal inference on observational data: difference-in-differences, regression discontinuity, interrupted time series, propensity methods.

  • Fluency in Python, including the ability to wrangle large, observational clinical datasets.

  • A track record of owning analyses or full research projects independently.

Bonus

  • Hands-on experience with EHR, claims, and billing data.

  • Familiarity with healthcare quality metrics and health system benchmarking.

  • Experience presenting research at conferences or to external audiences.

  • Exposure to claims or billing data.

  • Industry experience, though strong academic candidates are welcome.

Compensation and benefits

  • Salary: $170,000 to $215,000.

  • Equity: meaningful ownership in an early-stage company.

  • Healthcare: 100% of premiums covered.

  • PTO: unlimited, with a recommended minimum of 20 days.

  • 401(k): 4% match.

  • Equipment: laptop plus a home office budget.

Interview process

  • Intro call: get to know each other.

  • Technical: one or two interviews on your methods and past work.

  • Onsite: technical assessment, case study presentation, behavioral interview, meet the team.

  • Decision: same week as onsite. We respect your time. If there's a fit, you'll know fast!

If you're passionate about applying frontier AI to real-world impact, join us in building healthcare's future.

#J-18808-Ljbffr

Apply