Data Scientist
Nationwide Remote Office (US99), United States
ICF is looking for a Data Scientist with strong data engineering, statistics, machine learning, and predictive modeling skills to join our team. In addition, you will help develop AI-driven pilot projects and perform data analyses summarizing trends and modeling impacts for both internal and external clients.
The ability to work standard Eastern Time is expected.
What you’ll be doing:
- Conceptualize and develop custom AI-driven data pipelines which address client problems, maximize efficiency, and maintain high standards of quality.
- Design and develop statistical analyses, visualize the output of statistical models, present and interpret the output of predictive models, and perform quality assurance tasks on model code and output.
- Identify important and interesting questions about large datasets, then translate those questions into concrete analytical tasks.
- Build quantitative models with data, and communicate the results of those models to stakeholders
- Help conceptualize, as well as perform, data analyses to summarize trends
- Develop and execute database queries that in turn support developing/formatting modeling inputs
What you must have:
- Bachelor’s degree in a technical field: Computer Science, Engineering, or related discipline
- US Citizenship or Green Card. Employment must be compliant with eligibility for Public Trust due to Government Contract
- 2+ years of experience with NLP, anomaly detection, graph theory, deep learning principles and practices.
- 2+ years of experience with modeling and quantitative analysis using standard statistical software such as R, Python, SAS
- 2+ years of experience in SQL and DB programming
- 1+ years of experience working with any major cloud services (experience preferred with Sagemaker, Azure ML, VertexAI or similar)
What we’d like you to have:
- Familiarity with linux/unix environments and working from the command line
- Ability to obtain a security clearance
- Experience with incorporating Generative AI into data transformation pipelines
- Experience with Deep Learning capabilities
- Experience with data warehouse design and development as well as data modeling for both relational and dimensional data models
- Experience in reporting, story-telling and data visualization technologies such as Tableau, Shiny, Bokeh
- Demonstrated experience showing strong critical thinking and problem-solving skills paired with a desire to take initiative
- Excellent listening, written, and oral communication skills
- Ability to exercise independent judgment while effectively prioritizing and executing tasks while under pressure
- Team player with the ability to work in a fast-paced environment
Why you’ll love working here:
- Generous vacation and retirement plans
- Comprehensive health benefits
- Flexible work location
- Diverse workforce that values equality and inclusion
- Ongoing training and development opportunities
- Friendly community with lots of social events
- Participation in charity initiatives
- Employee support program
Working at ICF
ICF is a global advisory and technology services provider, but we’re not your typical consultants. We combine unmatched expertise with cutting-edge technology to help clients solve their most complex challenges, navigate change, and shape the future.We can only solve the world's toughest challenges by building an inclusive workplace that allows everyone to thrive. We are an equal opportunity employer, committed to hiring regardless of any protected characteristic, such as race, ethnicity, national origin, color, sex, gender identity/expression, sexual orientation, religion, age, disability status, or military/veteran status. Together, our employees are empowered to share their expertise and collaborate with others to achieve personal and professional goals. For more information, please read our EEO & AA policy.
Reasonable Accommodations are available, including, but not limited to, for disabled veterans, individuals with disabilities, and individuals with sincerely held religious beliefs, in all phases of the application and employment process. To request an accommodation please email Candidateaccommodation@icf.com and we will be happy to assist. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. Read more here: Requesting an Accommodation for the ICF interview process.
Read more about workplace discrimination rights, the Pay Transparency Statement, or our benefit offerings which are included in the Transparency in (Benefits) Coverage Act.
Candidate AI Usage Policy
At ICF, we are committed to ensuring a fair and equitable interview process for all candidates based on their own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) tools to generate or assist with responses during interviews (whether in-person or virtual) is not permitted. This policy is in place to maintain the integrity and authenticity of the interview process.
However, we understand that some candidates may require accommodations that involve the use of AI. If such an accommodation is needed, candidates are instructed to contact us in advance at candidateaccommodation@icf.com. We are dedicated to providing the necessary support to ensure that all candidates have an equal opportunity to succeed.
Pay Range - There are multiple factors that are considered in determining final pay for a position, including, but not limited to, relevant work experience, skills, certifications and competencies that align to the specified role, geographic location, education and certifications as well as contract provisions regarding labor categories that are specific to the position.
The pay range for this position based on full-time employment is:
$98,124.00 - $166,810.00Nationwide Remote Office (US99) ApplyJob Profile
Employment compliant with public trust eligibility Must be US citizen or green card holder
Benefits/PerksCharity initiatives Comprehensive health benefits Cutting-edge technology Diverse workforce Employee Support Program Equality Equal opportunity employer Fast-paced environment Flexible work Flexible work location Full-time Generous vacation Generous vacation and retirement plans Health benefits Inclusive workplace Ongoing Training Opportunity Participation in charity initiatives Reasonable accommodations Remote Remote-first company Retirement plans Social Events Training Training and Development Vacation
Tasks- Analysis
- Build quantitative models
- Communication
- Data visualization
- Design statistical analyses
- Develop ai-driven data pipelines
- Developing
- Development
- Execute database queries
- Exercise independent judgment
- Navigate change
- Perform quality assurance
- Quality assurance
- Reporting
- Shape the future
- Training
- Visualize statistical models
- Work in a fast-paced environment
AI AI tools Analyses Analysis Analytical Anomaly Detection Artificial Intelligence Azure Azure ML Bokeh Cloud Cloud Services Command Line Communication Critical thinking Database Programming Database queries Data engineering Data Modeling Data Pipelines Data Transformation Data Visualization Deep Learning Design Development Education Engineering Environment Formatting Generative AI Government Graph Theory Inclusion Integrity Linux Machine Learning ML Modeling NLP Oral communication Policy Predictive Modeling Problem-solving Process Programming Python Quality Assurance Quantitative Quantitative analysis R Reporting Sagemaker SAS Science Security Shiny SQL Statistics Tableau Technical Technology Technology Services Training Training and Development Transformation UNIX VertexAI Visualization WELL Workforce
Experience2 years
EducationArtificial Intelligence Bachelor Bachelor's degree Communication Computer Science Data Design Education Engineering Environment Government Health Policy Related discipline Relevant Work Experience Science Statistics Technical field Technology Training
CertificationsPublic Trust Security Clearance
TimezonesAmerica/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC-10 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9