Data Scientist

Brillient-Corporation; Hyattsville (MD); On-site; USD 120,000 - 140,000; Full time

Benefits offered by this job

Paid time off

Medical, Dental, and Vision Insurance

Company-Paid Life Insurance and Short‑

Voluntary Life Insurance and Long-Term

Employee Assistance Program (EAP)

Wellness Programs

401(k) Retirement Plan

Competitive Compensation

Job summary

Qualifications

• Bachelor's degree in data science or related technical field.
• Minimum five years of professional data science or analytics experience.
• Proficiency in Python, Jupyter Notebook, Pandas, NumPy, and scikit-learn.

Responsibilities

• Perform data preparation, cleaning, transformation, exploration, and feature engineering using Pandas and NumPy.
• Analyze large and complex datasets to identify trends, patterns, relationships, and actionable insights.
• Develop, implement, evaluate, and maintain statistical and machine learning models to support analytical and mission objectives.
• Evaluate model performance, validate results, and identify opportunities to improve model accuracy and reliability.
• Collaborate with technical teams, analysts, subject matter experts, and stakeholders to translate requirements into data-driven solutions.
• Develop and document analytical workflows and models using Jupyter Notebook.

Skills

Python programming

Data analysis

Machine learning

Communication

Collaboration

Analytical thinking

Education

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Technology

Tools

Jupyter Notebook

Pandas

NumPy

scikit-learn

OpenShift

Kubernetes

Shell scripting

Git

VS Code

Job description

Why Brillient?At Brillient, you'll join an award-winning digital transformation company dedicated to helping government agencies evolve from analog processes to digital solutions and advanced analytics that drive smarter decisions and mission success.We are guided by four core values:Value – Delivering meaningful results for our clients and employeesIntegrity – Building trust through honesty, accountability, and ethical business practicesFlexibility – Embracing agility and collaboration to adapt to changing needsInnovation – Continuously improving processes, technologies, and solutionsWe are committed to fostering a professional, respectful, and collaborative workplace where employees are supported, recognized for their contributions, and empowered to succeed.What Sets Us ApartCommitment to Sustainability: We strive to be an environmentally conscious organization through sustainable business practices.Community Impact: We believe in giving back and making a positive difference in the communities where we live and work.At Brillient, we hire talented, driven individuals who are passionate about helping clients achieve their mission objectives through innovation and excellence. As a client-focused and employee-centered organization, we take pride in our collaborative culture, commitment to professional growth, and dedication to delivering exceptional results.Benefits & Perks: We offer a comprehensive benefits package designed to support your well-being and work-life balance, including:Generous Paid Time OffMedical, Dental, and Vision InsuranceCompany-Paid Life Insurance and Short-Term Disability CoverageEmployee Assistance Program (EAP)Voluntary Life Insurance and Long-Term Disability CoverageWellness Programs401(k) Retirement PlanCompetitive CompensationThe Data Scientist will apply advanced analytical, statistical, and machine learning techniques to analyze complex datasets, develop predictive models, and generate actionable insights within a large data warehouse. The ideal candidate has strong hands-on ETL experience with Python and the broader data science ecosystem, including Jupyter Notebook, Pandas, NumPy, and machine learning frameworks such as scikit-learn.This role requires the ability to work independently with large and complex data sets and tables, translate business and mission requirements into analytical solutions, and communicate technical findings clearly to both technical and non-technical stakeholders.Key ResponsibilitiesPerform data preparation, cleaning, transformation, exploration, and feature engineering using Pandas and NumPy.Analyze large and complex datasets to identify trends, patterns, relationships, and actionable insights.Develop, implement, evaluate, and maintain statistical and machine learning models to support analytical and mission objectives.Evaluate model performance, validate results, and identify opportunities to improve model accuracy and reliability.Collaborate with technical teams, analysts, subject matter experts, and stakeholders to understand requirements and translate them into data-driven solutions.Use Python as the primary programming language for data analysis, modeling, automation, and data science applications.Develop and document analytical workflows and models using Jupyter Notebook.Develop and execute scripts to support data processing, automation, and analytical workflows.Apply machine learning techniques and frameworks, including scikit-learn, to develop and evaluate predictive and analytical models.Conduct exploratory data analysis and statistical analysis to support data-driven decision-making.Work with structured and unstructured data from multiple sources and formats.Develop repeatable and scalable analytical processes and workflows.Document methodologies, analytical approaches, models, assumptions, results, and recommendations.Present complex analytical findings and technical results in a clear and understandable manner.Work in both Linux and Windows operating environments.Work with containerized and/or distributed environments using OpenShift and Kubernetes.Maintain awareness of emerging data science, machine learning, and analytical technologies and identify opportunities to apply them to mission requirements.DISCLAIMER: The above statements are intended to describe the general nature and level of work performed. They are not intended to be an exhaustive list of all responsibilities, duties, skills, efforts, requirements, or working conditions. Management reserves the right to revise the job or to require that other or different tasks be performed as assigned in accordance with business demands and/or contractual requirements.Brillient is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to any status protected under applicable federal, state, or local law.Salary Range: $120,000-140,000Required Education & QualificationsBachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Technology, or a related technical field.US Citizenship RequiredMust be able to obtain and maintain a Public Trust security clearance as required by the contract.Minimum five (5) years of professional experience in data science, data analytics, statistical analysis, machine learning, or a related field.Strong hands-on experience with Python for data analysis, data science, and machine learning.Experience using Jupyter Notebook for data exploration, analysis, modeling, and documentation.Strong experience with Pandas and NumPy for data manipulation, analysis, and processing.Demonstrated experience developing and applying machine learning models, including experience with scikit-learn (sklearn) or comparable machine learning frameworks.Strong analytical and problem-solving skills, with the ability to work with complex datasets and develop data-driven solutions.Experience performing data cleaning, transformation, exploratory data analysis, feature engineering, and model evaluation.Experience working in Linux and Windows operating systems.Experience developing and using shell scripts for automation and data processing.Experience working with OpenShift and/or Kubernetes environments.Ability to communicate complex technical concepts, analytical findings, and recommendations effectively to technical and non-technical audiences.Ability to work independently and collaboratively in a fast-paced technical environment.Preferred Qualifications:Experience with Artificial Intelligence (AI), Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or model fine-tuning.Experience working with PostgreSQL/Postgres and/or Sybase IQ databases.Experience with Apache Airflow and automated ETL/data pipelines.Experience using Git, GitLab, and source control workflows.Experience using Visual Studio Code (VS Code) or similar integrated development environments.Experience deploying or operationalizing machine learning models in containerized or cloud environments.Experience with MLOps practices, model deployment, monitoring, and lifecycle management.