C
AI

Data Scientist III - TS/SCI w/poly clearance required

CyberTrend Engineering LLC · Annapolis Junction, MD, US

Actively hiring Posted 4 months ago

CyberTrend’s leadership has 40 years of experience in the industry, and the company continues to serve as a technology leader on many defense projects and programs. Formed in 2010, CyberTrend has long-standing partnerships and clients, including partners like AWS and IBM, government agencies, the intelligence community, and defense contractors. We provide talented and exceptionally qualified IT, architectural, system, and software engineering personnel.

Requires TS/SCI with Poly Clearance

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

The Data Scientist will support and contribute to the ever-growing complexity behind the data our customer analytics ingest. The Data Scientist will be able to analyze and provide insight in new and existing data sets; these insights will allow the customer to better implement and optimize analytic suites. The customer has plans to expand their analytic capabilities to utilize AI/ML along with graph-based technologies and frameworks.

  • 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.

Benefits:

  • Generous and competitive paid time off, scaled based on time in service, plus eleven paid annual holidays.
  • CyberTrend pays 100% of the cost for the following benefits for its full-time employees: including medical (base plan), dental, vision, disability, life, EAP, and more.
  • CyberTrend contributes 10% of your monthly gross salary to a SEP-IRA account. This retirement plan is non-contributory for the employee, has no vesting period, and is 100% owned and managed by the employee.
  • Educational assistance up to $5,250 annually for work-related acitivies upon prior approval
  • Training assistance up to $3,000 annually for work-related activities upon prior approval

CyberTrend provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

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