Senior/Staff Data Scientist (ACF)
S
SkylightGovernment data services
All work must be conducted within the U.S., excluding U.S. territories.Full-TimeStaff
SalaryStaff Data Scientist: $170,000–$203,000
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Job Details
- Required Skills
- Machine LearningMicrosoft Power BITableauData engineeringData scienceData visualizationDatabricks
Requirements
- Think strategically about data to identify questions, communicate ideas, surface opportunities, and support decisions.
- Be familiar with modern data engineering, including cleaning and preprocessing data from varied sources.
- Analyze datasets using appropriate methods and design, prototype, and build credible, effective, accessible statistical models.
- Preserve privacy and security when performing data analysis.
- Communicate data, models, and findings to technical and non-technical audiences.
- Use appropriate visualization tools to highlight actionable insights, trends, and recommendations.
- Champion leading practices in data science.
- Build small tools and automations with low-code and AI platforms such as Credal, DataBricks, and Microsoft Power Apps.
- Have experience working on cross-functional product, design, engineering, or operations teams in iterative delivery.
- Be able to obtain a Tier 2 public trust background investigation and successfully complete a company background check.
- For some federal-contract roles, have a degree or additional years of experience as a substitute.
Responsibilities
- Engage executive and program stakeholders to frame questions and find answers, including when the work is ambiguous.
- Organize data and build data pipelines using tools such as Palantir Foundry and PowerBI.
- Build AI agents, integrate them into workflows, and validate their outputs.
- Visualize grant and program data using Tableau and PowerBI.
- Analyze structured and unstructured information, including grants and program data, to discover trends and patterns.
- Build lightweight tools, prototypes, and automations with platforms such as Credal and Power Apps.
- Propose solutions for business challenges and select appropriate tools, frameworks, and languages.
- Communicate findings through visualizations that leadership can act on.
- Build predictive models and machine-learning algorithms when needed.
- Collaborate with user experience researchers and designers, product managers, engineers, and other specialists.
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