Data Scientist
Farm Credit Administration has an opening for a Data Scientist in Multiple Locations, United States. It is listed as a full-time position.
DGJ summary of this job
Our own short read of this listing, built only from the facts it gives. The employer’s original text follows further down.
Farm Credit Administration has an opening for a Data Scientist in Multiple Locations, United States. It is listed as a full-time position.
Skills and tools named in the text include SQL, Spark, Databricks, machine learning, statistics and research.
The listing gives the pay as $78,504 - $169,548 per year.
The advert does not mention visa sponsorship. If you would move to United States for this job, check the official work permit route first (DGJ Insight lists it where we have it).
Dev Global Jobs found this job on USAJobs on Nov 10, 2026; applications close on Dec 2, 2026.
- Employer
- Farm Credit Administration
- Location
- Multiple Locations, United States
- Job type
- Full-time
- Pay
- $78,504 - $169,548 per year
- Found
- Nov 10, 2026 on USAJobs
- Closes
- Dec 2, 2026
- Employer text
- 657 words, about 3 min to read
- Apply only on the official page (usajobs.gov). Dev Global Jobs is not the employer and never asks for a fee.
- Mirror the skills the advert names (SQL, Spark, Databricks and machine learning) in your CV where you really have them; applicant tracking systems look for these words.
- Plan to apply before Dec 2, 2026.
- Read the employer’s full text below (about 3 min) before you apply.
- Build or check your CV with the free DGJ CV Builder.
DGJ Insight
Our own data about this role and place, from official statistics and our live job index.
This job's listed pay is 43% above the benchmark.
Source: OECD Average annual wages, 2025
- H-1B specialty occupation: Employer petition, bachelor's degree or higher in the specialty; annual cap and lottery
- L-1 intracompany transferee: Employees of a related company abroad transferring to a US office
- O-1 extraordinary ability: Evidence of extraordinary ability in sciences, arts, education, business or athletics
Official routes: USCIS
About the role
Full text from the employer, as published on USAJobs, arranged into sections. Nothing added or removed.
Desired Qualification: Expert knowledge of and experience with using cloud-based data analytics, data engineering, or machine learning platforms, such as Databricks with hands-on experience utilizing Spark/PySpark, Delta Lake, or similar technologies, to independently develop, optimize, and maintain data workflows.
01Basic Requirements
A bachelor's or higher degree in Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position. OR Combination of education and experience: Courses equivalent to a major field of study (30 semester hours) as shown in paragraph A above, plus additional education or appropriate experience.
In addition to meeting the basic requirements, you must meet the specialized experience statement noted below. You qualify at the VH-38 (GS-12) level if you have one year of specialized experience equivalent to at least the VH-37 (GS-11) level in the Federal service, or comparable experience not gained through Federal service. Specialized experience is experience that has equipped you with the knowledge, skills, and abilities to perform the duties of the position.
Examples include analyzing data to identify risks, trends, or opportunities; conducting research and evaluating economic, financial, banking, agricultural, or related issues; and developing, maintaining, or using data analytics, machine learning, or data engineering tools to support business decisions.
You qualify at the VH-39 (GS-13) level if you have one year of specialized experience equivalent to at least the VH-38 (GS-12) level in the Federal service, or comparable experience not gained through Federal service. Specialized experience is experience that has equipped you with the skills, and abilities to perform the duties of the position.
Examples include analyzing data to identify risks, trends, or opportunities; conducting research and evaluating economic, financial, banking, agricultural, or related issues; and developing, maintaining, or using data analytics, machine learning, or data engineering tools to support business decisions, and leading projects while providing technical direction.
You qualify at the VH-40 (GS-14) level if you have one year of specialized experience equivalent to at least the VH-39 (GS-13) level in the Federal service, or comparable experience not gained through Federal service. Specialized experience is experience that has equipped you with the knowledge, skills, abilities and leadership to perform the duties of the position.
Examples include analyzing data to identify risks, trends, or opportunities; conducting research and evaluating economic, financial, banking, agricultural, or related issues; and developing, maintaining, or using data analytics, machine learning, or data engineering tools to support business decisions, and leading teams and strategic initiatives by using data-driven insights to influence stakeholders and outcomes.
Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., Peace Corps, AmeriCorps) and other organizations (e.g., professional; philanthropic; religious; spiritual; community, student, social). Volunteer work helps build critical competencies, knowledge, and skills and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.
Time-In-Grade Requirements: Current and former Federal employees (including VEOA eligibles) must have served one-year (52 weeks) at the next lower grade in the Federal service to meet time-in-grade restrictions per 5 CFR 300, Subpart F, by the closing date of the announcement.
As a Data Scientist you will apply advanced quantitative, computer science, mathematical, and statistical skills to interpret large structured and unstructured data sets to support financial and economic analyses of factors impacting FCS institutions or the System and changes in finance, banking, food sector, and general and rural economy.
Specific duties include: Architecting, deploying, and managing super intelligence (SI) and machine learning (ML) projects independently from conception to production, leveraging full-lifecycle expertise within the Databricks ecosystem. Developing, optimizing, and troubleshooting data and ML workflows utilizing PySpark, Spark SQL, and Delta Lake. Building and deploying autonomous agents for conversational data intelligence. Designing and implementing custom Retrieval-Augmented Generation (RAG) pipelines.
Analyzing a variety of data sources to provide data-driven insights to the organization.
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