Data Scientist

United States Consumer Product Safety Commission; Bethesda (MD); On-site; USD 80,000 - 120,000; Full time

Job summary

United States Consumer Product Safety Commission is seeking a Data Scientist to turn raw information into actionable insights. You will wrangle data, clean datasets, and improve quality while experimenting with machine learning and AI to detect product-safety risks before they arise.

Applicants must have 52 weeks of specialized federal experience and will be evaluated on the ability to develop models, build data pipelines in the cloud, and communicate findings to diverse stakeholders.

Qualifications

• 52 weeks of specialized experience equivalent to the next lower grade level in the Federal Service.
• Experience in statistical, AI/ML, NLP models to analyze complex data.
• Ability to build cloud-based data pipelines using Python/SQL and create analytical products.
• Experience producing dashboards and communicating insights to diverse stakeholders.

Responsibilities

• Transform raw information into meaningful insights to protect consumers.
• Wrangle, clean, and improve quality of key datasets.
• Experiment with ML/AI techniques to spot product-safety risks.
• Present data-driven findings to stakeholders with clarity.

Skills

AI/ML models

NLP models

Python

SQL

Data visualization

Cloud data pipelines

Dashboarding

Tools

Python

SQL

ETL/ELT

Cloud environments

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. 1) Experience developing statistical, AI/ML, and NLP models to analyze complex structured and unstructured data;
2. 2) Building cloud-based data pipelines and using Python/SQL to create and evaluate analytical products;
3. 3) Producing dashboards and visualizations and communicating data-driven insights to diverse stakeholders.

GS-13:

1. 1) Experience applying advanced statistical, mathematical, and scientific methods to design, develop, and evaluate analytical and predictive models using complex, large-scale datasets;
2. 2) Experience developing and implementing advanced statistical methodologies, AI/ML, NLP, and cloud-based analytical solutions to address complex, high-impact data problems;
3. 3) Performing data acquisition, transformation, and integration using modern ETL/ELT, data modeling, and workflow orchestration practices in cloud environments;
4. 4) Designing data visualizations, dashboards, and data storytelling products that communicate complex analytical findings clearly to diverse audiences, including uncertainty and method limitations;
5. 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.