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

ICF

Senior Manager, Commercial Energy

Santa Fe, NM · On-site +1

Oversee program evaluation, including analysis, data collection, and reporting. * Provide resource ... Bachelor's Degree in Energy, Business, Environmental Sciences, Engineering, Economics, Policy or a ...

All JobsData Science JobsRemote Data Science JobsRemote Data Science Jobs in Santa Fe, NM

Remote Data Science information

See Santa Fe, NM salary details

$22.8K

$101.2K

$193.1K

How much do remote data science jobs pay per year?

As of Aug 10, 2026, the average yearly pay for remote data science in Santa Fe, NM is $101,205.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,277.00 and $140,373.00 per year, depending on experience, location, and employer.

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

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, often supported by a relevant degree. Expertise in programming languages such as Python or R, familiarity with machine learning libraries, and experience with cloud-based data platforms are typically required. Excellent communication, self-motivation, and time management skills help you effectively collaborate and deliver results in a remote environment. These skills ensure accurate data analysis, meaningful insights, and successful teamwork despite physical distance.

How do remote data scientists typically collaborate with cross-functional teams to deliver insights?

Remote data scientists often work closely with product managers, engineers, and business analysts using digital collaboration tools such as Slack, Zoom, and project management platforms. Regular virtual meetings, code sharing via Git repositories, and clear documentation are essential to ensure alignment and transparency. While working remotely can present challenges in communication, proactive updates and scheduled syncs help foster strong teamwork and keep projects on track.

What is remote data science?

Remote data science refers to the practice of performing data analysis, modeling, and interpretation tasks from a location outside of a traditional office, such as from home or a co-working space. Remote data scientists use tools like Python, R, and SQL to analyze data, build predictive models, and communicate insights to stakeholders, all while collaborating virtually with their teams. This setup offers flexibility and can increase access to global job opportunities, but also requires strong self-motivation and communication skills to be effective.

What are the qualifications to get a remote data science job?

The qualifications for a remote data scientist depend in large part on your employer and their industry. Most employers expect remote data science professionals to have at least a bachelor’s degree in statistics, math, computer science, or a related field. Some expect postgraduate degrees in a field like data mining or machine learning or demonstrable skills in these areas. As a remote worker, you need access to relevant programs and an internet connection. You may also want to pursue certification, such as becoming a Certified Analytics Professional (CAP).

Can I work remotely as a remote data scientist?

Yes, many remote data scientist positions are available, allowing professionals to work from anywhere with a reliable internet connection. These roles often require skills in programming, data analysis, and familiarity with tools like Python, R, or SQL, and may involve collaboration through online platforms. Remote work arrangements are common in the data science field, especially with the increasing adoption of cloud-based tools and flexible schedules.

What is the difference between Remote Data Science vs Remote Data Analyst?

AspectRemote Data ScienceRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills in Python/R; knowledge of machine learningDegree in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves building models and algorithmsData reporting, visualization, and interpreting data trends for decision-making
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, retail, finance, healthcare

Remote Data Science involves developing predictive models and advanced analytics, requiring programming and machine learning skills. Remote Data Analysts focus on interpreting data, creating reports, and visualizations. While both roles analyze data remotely, Data Scientists typically handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and reporting.

More about Remote 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 job categories do people searching Remote Data Science jobs in Santa Fe, NM look for? The top searched job categories for Remote Data Science jobs in Santa Fe, NM are:
What cities near Santa Fe, NM are hiring for Remote Data Science jobs? Cities near Santa Fe, NM with the most Remote Data Science job openings:
Remote Data Science jobs near you
Infographic showing various Remote Data Science job openings in Santa Fe, NM as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $101,205 per year, or $48.7 per hour.

Solutions Architect SAP Data Migration

Coastal International Security, Inc

Los Alamos, NM • Remote

$98 - $103/hr

Full-time

Posted 17 days ago

Job description

Solutions Architect 4 - SAP Data Migration (DOE/LANL)Location: Remote, supporting LANL's SAP S/4HANA modernization initiativeCitizenship: U.S. Citizenship RequiredCompensation: $98 - $103/hrWhy This RoleLANL is undertaking a greenfield SAP S/4HANA modernization effort and needs a senior, client-side data migration authority who can stand shoulder to shoulder with the System Integrator's data lead as a technical peer. This is not a general data architecture role. It requires someone who has led enterprise SAP data migrations from the inside of a major System Integrator and has since moved into client-side advisory work, someone who knows when to challenge an SI's approach, when to accept their judgment, and when to hold position. You will own the day to day execution of the client's data workstream while also serving as an independent, senior voice on migration architecture, data quality, and go live readiness.Key ResponsibilitiesAdvisory & OversightServe as the client side senior authority on SAP data migration, facing off to the System Integrator's data lead as a technical peerReview and challenge the SI's data migration approach where it carries unnecessary risk, cost, or downstream operational burdenAdvise on migration architecture for greenfield S/4HANA from non-SAP sources, including legacy concept to SAP concept mapping and tooling trade offsHands-on Coordination & DeliveryOwn day to day execution coordination of the client side data workstream across all domainsServe as the daily point of contact with the SI's data migration team, tracking deliverables and escalating delaysRun working sessions with client data owners and the integrator's team, driving open actions and decisions to closureData Quality & ReconciliationSet and monitor cleansing standards across data domains, validating that the SI's quality criteria are fit for go liveOrganize and track mock load cycles and review reconciliation results independently of the SISurface data quality risks the SI may not flag, including missing legacy concepts and silent data loss in transformationGovernance & CutoverEnsure data migration activities comply with data classification policy and applicable regulatory requirementsMaintain the data migration cutover plan and prepare data readiness inputs for go or no go decisionsSupport hypercare on data related issues post go live, and provide migration status reporting to program leadershipRequired Qualifications15+ years leading enterprise SAP data migration workstreams, with at least 4 full lifecycle S/4HANA programs delivered end to end, greenfield preferredExperience running the data workstream from inside a major System Integrator, followed by client side advisory workDeep hands on experience migrating from non-SAP sources (Oracle EBS, JD Edwards, PeopleSoft, custom systems) into SAPFull scope enterprise migration experience spanning Finance, Supply Chain, HR/HCM, Plant Maintenance / EAM, and Master DataDeep understanding of S/4HANA data models, business partner concept, universal journal, and material ledgerStrong grounding in data migration methodology, including ETL design, reconciliation, cutover sequencing, and hypercare supportHands on exposure to at least one regulated compliance framework (HIPAA, SOC 2, PCI-DSS, GDPR, or FedRAMP), with demonstrated ability to translate requirements into migration controlsExcellent communication, able to move fluidly from executive readouts to deep technical review with the SI's engineersNice to HavePrior experience with Oracle EBS as the source systemFamiliarity with SAP Business Data Cloud (BDC), Databricks, or Snowflake as staging/reconciliation environmentsSAP certifications (S/4HANA, Data Migration, or comparable)Experience in audit heavy sectors such as financial services, healthcare, life sciences, pharma, or governmentMandatory Requirements - Read Before ApplyingS. Citizenship required15+ years leading enterprise SAP data migration workstreams required, with at least 4 full lifecycle S/4HANA programs delivered end to endMust have worked the data migration workstream from inside a major System Integrator, followed by client side advisory work, candidates without this specific career path will not be consideredMust have direct, hands on experience migrating from non-SAP sources (Oracle EBS, JD Edwards, PeopleSoft, or custom systems) into SAPMust have hands on exposure to at least one regulated compliance framework (HIPAA, SOC 2, PCI-DSS, GDPR, or FedRAMP) applied to data migration controls