Data Scientist (Partial Telework)

GliaCell Technologies•Annapolis Junction, MD

54d•$115,000 - $190,000•Hybrid

About The Position

GliaCell is seeking a Data Scientist on one of our subcontracts. This is a full-time position offering the opportunity to support a U.S. Government customer. The mission is to provide technical expertise that assists in sustaining critical mission-related software and systems to a large government contract.

Requirements

Possess an active or rein-statable TS/SCI with Polygraph security clearance. (This position requires in-scope poly, within 7 years).
U.S. Citizenship.
5+ years of experience and a Bachelor's Degree in Computer Science or a related discipline.
Possess software development skills
Work well independently as well as on a team.
Strong communication 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 NumPy 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 TensorFlow 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 PostgreSQL and MongoDB) 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.