Data Scientist

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 employees

Integrity – Building trust through honesty, accountability, and ethical business practices

Flexibility – Embracing agility and collaboration to adapt to changing needs

Innovation – Continuously improving processes, technologies, and solutions

We 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 Apart Commitment 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 Off Medical, Dental, and Vision Insurance Company-Paid Life Insurance and Short-Term Disability Coverage Employee Assistance Program (EAP)
Voluntary Life Insurance and Long-Term Disability Coverage Wellness Programs
401(k) Retirement Plan Competitive Compensation The 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, Num Py, 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 Responsibilities Perform data preparation, cleaning, transformation, exploration, and feature engineering using Pandas and Num Py.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…