AI/ML Analyst

The AI/ML Analyst will be responsible for analyzing data and developing machine learning models to enhance decision-making processes across various projects. This role involves collecting, processing, and analyzing large datasets to extract insightful patterns and trends. The analyst will collaborate with cross-functional teams to implement AI solutions and provide actionable recommendations based on model outputs.

Key Responsibilities:

• Develop and implement machine learning algorithms and models to solve complex problems.
• Conduct data preprocessing and data cleaning to ensure high-quality inputs for analytical activities.
• Analyze and interpret data, making recommendations for improvements and optimization.
• Collaborate with software engineers and data scientists to integrate AI solutions into software applications.
• Create clear documentation of algorithms, methodologies, and reports on analysis findings.
• Stay updated on the latest trends and advancements in AI and machine learning technologies.
• Provide training and support to end users regarding AI tools and applications.

• Three (3) years of professional experience developing and implementing AI models and algorithms to address complex business and mission challenges.
• Programming proficiency (e.g., Python, R, SQL, Java, Scala, C++, Tableau).
• Experience and understanding of machine learning (ML) and related algorithms (e.g., linear regression, logistic regression, decision trees, random forests, support vector machines, and gradient boosting methods), unsupervised learning (e.g. clustering algorithms (K-Means, hierarchical clustering, DBSCAN), dimensionality reduction techniques (e.g., PCA, t-SNE), and anomaly detection methods, and familiarity with reinforcement learning principles.
• Understand the architecture and training of different types of neural networks (e.g., feedforward networks, convolutional neural networks, recurrent neural networks, transformers).
• Experience building, training, and deploying deep learning models, familiarity with Natural Language Processing techniques such as but not limited to text classification, sentiment analysis, named entity recognition, and topic modeling.
• Knowledge of object detection, image segmentation, and image classification.
• Knowledge of Data Wrangling and Preprocessing, Statistical Analysis, Model Evaluation and Selection, Model Deployment and Monitoring, Big Data Technologies, and Data Visualization (e.g. Tableau, Power BI, Matplotlib, Seaborn). Collaborate with data engineers to preprocess and clean data for AI models. Create and maintain documentation for AI models, algorithms, and workflows.
• Troubleshooting and resolving issues related to AI systems. Report findings and recommendations to stakeholders, including technical and non-technical audiences. 
• Must have an active Secret Clearance.

• Health Care Plan (Medical, Dental & Vision)
• Retirement Plan (401k)
• Life Insurance (Basic, Voluntary & AD&D)
• Paid Time Off (Vacation, Sick & Public Holidays)
• Short Term & Long Term Disability