Data Scientist Security Clearance

Position: Data Scientist with Security Clearance
Location: Annapolis Junction

Job Description Base-2 Solutions is seeking a Data Scientist will develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers;

partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows. Required Skills
* Programming

Languages:

* Proficiency in programming languages such as Python and R is crucial for data manipulation, analysis, and implementing algorithms.

* Python is favored for its simplicity and extensive libraries (like Num Py and pandas), while R is preferred for statistical analysis and data visualization.

* Statistical Analysis:
* A strong foundation in statistics and probability is necessary for analyzing data accurately and making informed decisions.
* Understanding concepts like regression analysis, hypothesis testing, and statistical distributions is essential.
* Machine Learning:
* Knowledge of machine learning algorithms and frameworks (such as Tensor Flow and Scikit-Learn) is vital for building predictive models and automating decision-making processes.
* Data Wrangling:
* The ability to clean and organize complex datasets is critical.
* Data wrangling involves transforming raw data into a usable format, which is often time-consuming but necessary for effective analysis.
* Database Management:
* Familiarity with SQL and database management systems (like Postgre

SQL and Mongo

DB) is essential for extracting and manipulating data stored in relational databases.
* Data Visualization:
* Skills in data visualization tools (such as Tableau and Matplotlib) help communicate findings effectively.
* Creating charts, graphs, and dashboards is crucial for making data understandable to stakeholders. Qualifications
* Bachelor's degree from an accredited college or university in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science).
* Five (5) years of experience analyzing datasets and developing analytics, five (5) years of experience programming with data analysis software such as R, Python, SAS, or MATLAB.
* An additional four (4) years of experience in software development, cloud development, analyzing datasets, or developing descriptive, predictive, and prescriptive analytics can be substituted for a Bachelor's degree.
* A PhD from an accredited college or university in a quantitative discipline can be substituted for four (4) years of experience. Capabilities
* Produce data visualizations that provide insight into dataset structure and meaning.
* Work with subject matters experts (SMEs) to identify important information in raw data and develop scripts that extract this information from a variety of data formats (e.g., SQL tables, structured metadata, network logs).
* Incorporate SME input into feature vectors suitable for analytic development and testing.
* Translate customer qualitative analysis process and goals into quantitative formulations that are coded into software prototypes.
* Develop and implement statistical, machine learning, and heuristic techniques to create descriptive, predictive, and prescriptive analytics.
* Develop statistical tests to make data-driven recommendations and decisions.
* Develop experiments to collect data or models to simulate data when required data are unavailable.
* Develop feature vectors for input into machine learning algorithms.
* Identify the most appropriate algorithm for a given dataset and tune input and model parameters.
* Evaluate and validate the performance of analytics using standard techniques and metrics (e.g. cross validation, ROC curves, confusion matrices).
* Oversee the development of individual analytic efforts and guide team in analytic development process.
* Guide…