Data Scientist

Ignite Digital•Chesapeake, VA

2h•$120,000

About The Position

Ignite Digital is seeking an experienced Data Scientist to support a U.S. Navy customer in the Norfolk, Virginia area. The role is suited to an analytical, detail-oriented professional who can work in data-driven environments and translate complex analytical insights into actionable outcomes for technical and non-technical stakeholders. The Data Scientist will use advanced statistical methods, machine learning techniques, and data engineering practices to address mission and business challenges within a Naval program environment.

Requirements

At least 4 years of professional experience in data analysis, data science, or a related field.
Proficiency in Python or R.
Experience with data science libraries such as Pandas, NumPy, and Scikit-learn.
Strong SQL skills and experience with relational or NoSQL databases.
Hands-on experience with data visualization tools such as Tableau, Power BI, Matplotlib, or Seaborn.
Understanding of statistical modeling, including regression, classification, and clustering.
Experience developing and deploying machine learning models.
Strong analytical thinking, problem-solving, and organizational skills.
Exceptional communication skills and ability to manage multiple tasks effectively.
Active DoW SECRET clearance.
Bachelor’s or master’s degree in a quantitative field such as computer science, statistics, mathematics, engineering, or economics.

Nice To Haves

Familiarity with cloud-based machine learning platforms such as AWS SageMaker, Azure ML, or Google Cloud AI.
Experience with big data systems such as Hadoop or Spark.
Relevant professional certifications in cloud, data science, machine learning engineering, or analytics.

Responsibilities

Gather data from multiple sources, including databases, APIs, and web scraping activities.
Clean, transform, and prepare datasets for analysis.
Develop and maintain automated data pipelines.
Implement data quality checks, validation, and anomaly detection procedures.
Conduct exploratory data analysis to extract insights, identify patterns, and detect anomalies.
Build, optimize, and evaluate statistical models and machine learning algorithms, including supervised, unsupervised, and deep learning methods.
Perform A/B testing and other experimental designs to evaluate solution efficacy.
Improve model accuracy, reliability, and performance.
Communicate analytical findings clearly to technical and non-technical audiences.
Develop reports, presentations, dashboards, and visualizations to support decision-making.
Create tools to monitor key metrics and operational performance.
Document methodologies, models, results, and code.
Collaborate with data scientists, engineers, analysts, and mission stakeholders.
Keep current with emerging technologies, data science trends, and toolsets.
Participate in code reviews, knowledge-sharing sessions, and team development activities.
Identify mission and business problems suited to data-driven solutions and contribute to solution design.
Troubleshoot and resolve data-related and pipeline issues.