Description

Duties As a Data Scientist, you will: Collaborate with team members, subject matter experts, or stakeholders, as needed, to identify and select relevant data sources to perform duties. Obtain, evaluate, and interpret data extracts and reports from various systems, assessing relevant data source validity and reliability to meet project needs. These datasets come from diverse sources and in diverse forms that include computerized statistical files, manual or automated program reporting systems, program files, and ad hoc information obtained from internal and external sources. Ensure data sources are fit for their intended purpose through assessment of potential data quality issues, such as bias in data ingestion or transmission mechanisms. Data sources commonly used in this role include financial system data, demographic data and program outcome data as well as unstructured and narrative information found in program or policy utilization reports, safety systems, economic and social indicators, environmental impacts and other qualitative and quantitative research. Use software and/or programming languages such as R, Python, SQI, Tableau and/or PowerBI, to transform, combine, and clean data preparation for analysis. Apply appropriate data wrangling techniques, such as probabilistic, matching and imputation of missing values, to clean and prepare imperfect datasets. Work with teams to develop suitable datasets for ad hoc and ongoing analytic uses, with an emphasis on long term automation and replicability where appropriate Independently analyze data leveraging suitable statistical and mathematical methodologies. Be familiar with methods of exploratory data analysis, selecting appropriate models and identifying when data is insufficient to reach valid conclusions. Conduct observational and statistical analysis using appropriate software and/or programming languages to test hypotheses, predict outcomes, and inform decisions. Be comfortable working with large semi-structured and unstructured datasets and numerous confounding variables. Solve technical problems by choosing appropriate tools and techniques. Be able to explain any data structures or quality constrains impacting the study designs to both technical and non-technical audiences. The ideal candidate will have demonstrated experience analyzing data to support policy and operational decisions and will contribute to project teams using outstanding analytical and problem-solving skills, performing sophisticated data analysis, and developing data visualizations, online databases, and mobile applications to support research and communications initiatives. The candidate will possess excellent interpersonal skills, creativity, resourcefulness and organization. Help Requirements Conditions of Employment You must be a U.S. citizen & meet specialized experience to qualify Submit application and resume online by 11:59 PM EST on the closing date Required documents must be submitted by the closing date. Direct Hire Authority will be used to fill this position CONDITIONS OF EMPLOYMENT: SELECTIVE SERVICE: Males born after 12/31/1959 must be registered for the Selective Service. GOVERNMENT TRAVEL CARD: This position involves travel. A government contractor-issued travel card will be issued and must be retained for official business only. PROBATIONARY PERIOD: Applicants may be required to successfully complete a one-year probationary period (unless already completed). TELEWORK ELIGIBILITY: This position may be eligible for occasional and/or regularly scheduled telework. The number of telework days approved will be determined by your immediate supervisor or manager following the agency’s telework policy and guidance. If participating in the telework program, you will be required to sign a telework agreement detailing agency telework policy requirements, working conditions, and expectations for the position. POSITION SENSITIVITY AND RISK: Varies by position and will be based on the position to which appointed. SECURITY CLEARANCE: Varies by position. If applicable, you must be able to obtain and maintain the appropriate security clearance of the position to which appointed. FINANCIAL DISCLOSURE: Varies by position. If applicable, the applicant selected is required to submit a Confidential Financial Disclosure Report (OGE Form 450) within 30 days of appointment and annually thereafter. FOR DIRECT HIRE CANDIDATES: You must complete a one-year probationary period (unless already completed). REMOTE WORK: This position may be eligible for remote work, which does not require reporting to the agency worksite location on a regular basis. If selected for a remote work location, you will be required to sign a remote work agreement detailing agency remote work policy requirements, working conditions, and expectations for the position. Qualifications To meet the minimum qualifications for this position, you must (1) meet the Education Requirement for the series, (2) provide a copy of transcripts for verification, AND (3) meet either the education or experience qualifications for the grade at which you are requesting consideration. To qualify for the GS-11 on Experience, you must have at least one year of experience equal or equivalent to the GS-09 it must include: Experience using data science tools, techniques and technologies to process large, datasets into structured formats for matching, analysis, or estimation. Experience using data science knowledge in reviewing, formatting, analyzing, and providing information from multiple systems for data reports and projects and presenting results to individuals and groups such as managers, clients, professional organizations, and/or other groups and individuals. To qualify for the GS-11 on Education alone, you must have: 3 years of progressively higher level graduate education leading to a Ph.D. degree or Ph.D. or equivalent doctoral degree. You can also qualify based on a combination of higher level graduate education and experience. This must be fully supported by your resume and transcripts, provided with your application. To qualify for the GS-12 on Experience, you must have at least one year of experience equal or equivalent to the GS-11 it must include: Experience using data science tools, techniques and technologies to process large, datasets into structured formats for matching, analysis, or estimation. Experience using data science knowledge in reviewing, formatting, analyzing, and providing information from multiple systems for data reports and projects and presenting results to individuals and groups such as managers, clients, professional organizations, and/or other groups and individuals. You cannot qualify on education at the GS-12 level; you must have experience. To qualify for the GS-13 on Experience, you must have at least one year of experience equal or equivalent to the GS-12 it must include: Experience applying statistical analysis to determine and/or confirming technical validity and acceptability (fitness-for-use) of new or combined data sources, machine learning outputs, and/or data science methods. Experience leading projects using data science tools, techniques and technologies to process large datasets into structured formats for matching, analysis, or estimation. You cannot qualify on education at the GS-13 level; you must have experience. To qualify for the GS-14 on Experience, you must have at least one year of experience equal or equivalent to the GS-13 it must include: Experience in the designing and developing of data analytics/science related products using data science tools, techniques and technologies. Experience managing full life cycle data science projects, identifying technical validity and acceptability (fitness-for-use) of products and providing appropriate recommendations for utilization. You cannot qualify on education at the GS-14 level; you must have experience. KNOWLEDGE, SKILLS AND ABILITIES (KSAs): Your qualifications will be evaluated on the basis of your level of knowledge, skills, abilities and/or competencies in the following areas: Knowledge of data science theory and utilization sufficient to serve as a contributor in the development of analysis and the application of data science solutions to assess the safety, economic, social or environmental impacts of transportation. Knowledge of and skill in applying statistical theories and methods used in the acquisition, collection, evaluation, classification, and analysis of nationwide navigation data to develop new and improved method. Ability to support the development of algorithms, programs, relational databases and systems architecture sufficient to utilize them in the planning, development, and execution of data science applications solutions to transportation policy issues. Ability to acquire, update, and integrate large datasets from diverse sources to address key transportation issues. Skill with one or more programming languages, and one or more spatial analysis tools (Python, R, ArcGIS, SQL). For all types of consideration, 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 For additional information about applying to Federal positions, please click on the following link: https://www.opm.gov/policy-data-oversight/classification-qualifications/general-schedule-qualification-policies/#url=e4 Students enrolled in a qualifying degree program can apply if the anticipated graduation date is within six months of closing date of the announcement. Graduation transcript must be received before start date. Other applicants must meet all qualification requirements by the closing date of this announcement. Education Basic Requirements: Degree: 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.

Role and Responsibilities

• As a Data Scientist, you will: Collaborate with team members, subject matter experts, or stakeholders, as needed, to identify and select relevant data sources to perform duties. Obtain, evaluate, and interpret data extracts and reports from various systems, assessing relevant data source validity and reliability to meet project needs. These datasets come from diverse sources and in diverse forms that include computerized statistical files, manual or automated program reporting systems, program files, and ad hoc information obtained from internal and external sources. Ensure data sources are fit for their intended purpose through assessment of potential data quality issues, such as bias in data ingestion or transmission mechanisms. Data sources commonly used in this role include financial system data, demographic data and program outcome data as well as unstructured and narrative information found in program or policy utilization reports, safety systems, economic and social indicators, environmental impacts and other qualitative and quantitative research. Use software and/or programming languages such as R, Python, SQI, Tableau and/or PowerBI, to transform, combine, and clean data preparation for analysis. Apply appropriate data wrangling techniques, such as probabilistic, matching and imputation of missing values, to clean and prepare imperfect datasets. Work with teams to develop suitable datasets for ad hoc and ongoing analytic uses, with an emphasis on long term automation and replicability where appropriate Independently analyze data leveraging suitable statistical and mathematical methodologies. Be familiar with methods of exploratory data analysis, selecting appropriate models and identifying when data is insufficient to reach valid conclusions. Conduct observational and statistical analysis using appropriate software and/or programming languages to test hypotheses, predict outcomes, and inform decisions. Be comfortable working with large semi-structured and unstructured datasets and numerous confounding variables. Solve technical problems by choosing appropriate tools and techniques. Be able to explain any data structures or quality constrains impacting the study designs to both technical and non-technical audiences.