Responsibilities:

1. Help manage a team to:
2. Collect, clean, and preprocess large volumes of structured and unstructured data from various sources.
3. Perform exploratory data analysis to identify patterns, trends, and anomalies in the data.
4. Develop and implement machine learning models and algorithms to solve business problems and optimize processes.
5. Evaluate model performance and iteratively improve model accuracy, scalability, and efficiency.
6. Stay up-to-date with the latest advancements in data science, machine learning, and artificial intelligence, and identify opportunities to apply them to our business.
7. Collaborate with stakeholders to define project objectives, requirements, and success criteria.
8. Communicate findings and insights to non-technical stakeholders through data visualizations, reports, and presentations.

Requirements:

1. TS/SCI Clearance
2. Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field. Master's or Ph.D. preferred.
3. Experience in data science, machine learning, or a similar role.
4. Proficiency in programming languages such as Python or R.
5. Strong background in statistical analysis and machine learning techniques.
6. Experience with data manipulation and visualization libraries (e.g., pandas, matplotlib, seaborn).
7. Familiarity with machine learning frameworks and libraries (e.g., scikit-learn, TensorFlow, PyTorch).
8. Experience with SQL and relational databases.
9. Excellent problem-solving and analytical skills.
10. Strong communication and collaboration skills, with the ability to work effectively in a team environment.

Preferred Qualifications:

1. Experience with big data technologies (e.g., Hadoop, Spark) and distributed computing frameworks.
2. Knowledge of natural language processing (NLP) techniques and tools.
3. Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
4. Familiarity with data visualization tools (e.g., Tableau, Power BI).
5. Experience with agile development methodologies.