Data Scientist

Consumer Product Safety Commission; Bethesda (MD); On-site; USD 90,000 - 130,000; Full time

Job summary

Consumer Product Safety Commission in Bethesda, MD seeks a Data Scientist to transform raw data into meaningful insights that protect consumers nationwide. The role involves wrangling data, cleaning datasets, and using ML/NLP to spot emerging product-safety risks.

Strong emphasis on Python/SQL, cloud pipelines, and communicating results to stakeholders. Applicants must meet the specialized experience requirement, including building data pipelines, developing models, and producing dashboards,

Qualifications

• Experience with statistical, AI/ML, and NLP models.
• Experience building cloud-based data pipelines using Python/SQL.
• Ability to produce dashboards and communicate insights to stakeholders.

Responsibilities

• Analyze complex structured and unstructured data to generate insights.
• Develop and evaluate analytical and predictive models for risk identification.
• Design data visualizations and dashboards for diverse audiences.

Skills

Python

SQL

AI/ML

NLP

Data visualization

Cloud data pipelines

ETL/ELT

Job description

As a Data Scientist in CPSC's Analytics Center of Excellence, you'll transform raw information into meaningful insights that help protect consumers nationwide. One moment they're wrangling data-acquiring, cleaning, and improving the quality of key datasets-and the next they're experimenting with machine learning and AI techniques to spot emerging product-safety risks before they become problems.

In addition to the mandatory education requirement, all applicants must have 52 weeks of specialized experience equivalent to at least the next lower grade level in the Federal Service. Specialized experience is experience that has equipped the candidate with the particular knowledge, skills, and abilities to perform successfully the duties of the position. Qualifying specialized experience must demonstrate the following: GS-12: 1) Experience developing statistical, AI/ML, and NLP models to analyze complex structured and unstructured data; 2) Building cloud-based data pipelines and using Python/SQL to create and evaluate analytical products; and 3) Producing dashboards and visualizations and communicating data-driven insights to diverse stakeholders. GS-13: 1) Experience applying advanced statistical, mathematical, and scientific methods to design, develop, and evaluate analytical and predictive models using complex, large-scale datasets; 2) Experience developing and implementing advanced statistical methodologies, AI/ML, NLP, and cloud-based analytical solutions to address complex, high-impact data problems; 3) Performing data acquisition, transformation, and integration using modern ETL/ELT, data modeling, and workflow orchestration practices in cloud environments; 4) Designing data visualizations, dashboards, and data storytelling products that communicate complex analytical findings clearly to diverse audiences, including uncertainty and method limitations; and 5) Programming in Python and SQL and applying industry-standard ML and analytical libraries to develop production-ready analytical solutions. Evidence of the above specialized experience must be supported by detailed documentation of duties performed in positions held. Your resume is the key means we have for evaluating your skills, knowledge, and abilities as they relate to this position. Therefore, we encourage you to be clear and specific when describing your experience. We will not make assumptions regarding your experience or based on job titles alone. If your resume does not support your questionnaire answers, we will not allow credit for your response(s). 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. Applicants must meet the qualifications for this position by the closing date of this announcement.