Senior Data Scientist / Machine Learning Engineer

GliaCell Technologies•Annapolis Junction, MD

5d•$170,000 - $260,000

About The Position

GliaCell is seeking a Senior 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.
Bachelor's degree or higher from an accredited college or university in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science). A minimum of ten (10) years of experience in two (2) or more of the following: designing/implementing machine learning, data mining, advanced analytical algorithms, advanced statistical analysis, artificial intelligence, or software engineering 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 Master’s Degree from an accredited college or university in a quantitative discipline can be substituted for two (2) years of experience for a total of eight (8) years of experience required. A Doctoral Degree from an accredited college or university in a quantitative discipline can be substituted for four (4) years of experience for a total of six (6) years of experience required.
Work well independently as well as on a team.
Strong communication skills.
Requires significant Machine Learning Operations / Data Science background.

Responsibilities

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 analytic development toward solutions that can scale to large datasets
Partner with software engineers and cloud developers to develop production analytics
Develop and train machine learning systems based on statistical analysis of data characteristics to support mission automation
Lead a team of data scientists in the development of multiple analytic efforts
Work with customers and SMEs to define analytic requirements and guide the team in formulating analytics that meet requirements
Guide the transition of prototyped analytics to production system
Understand emerging machine learning and pattern recognition algorithms and guide a team of data scientists in integrating state-of-the-art algorithms into solutions
Delegate analysis responsibilities to one or more team members and monitor performance