Who we are:
At Applied Network Solutions (ANS), we bring together some of the most curious minds in networking and cybersecurity. ANS was founded to disrupt the status quo. For over 20 years, our team provides expertise in network, system engineering and both offensive and defensive cybersecurity operations.
What we do:
Our vision is for a future in which talent and customers alike come to ANS because of our reputation for delivering technical excellence, solving our nation’s toughest challenges and our ability to exceed expectations.
Why ANS:
At ANS we value the integrity of your work. We are looking for the right person to plan, analyze, design, develop, test, secure, integrate, implement, operate, and maintain the custom solutions that ANS delivers. Together, let’s ensure today is safe and tomorrow is smarter.
As a Data Scientist on our team, you will: Be trusted to design and execute machine learning models and applications, document analytic results and create visualizations for client stakeholders.
Requirements:
- Active TS/SCI clearance with Polygraph
- A Bachelor's degree and 10 years of relevant experience. A Master's degree and 8 years of relevant experience. A Doctorate's degree and 6 years of relevant experience. An Associate's degree plus 12 years of relevant experience may be considered for individuals with in-depth experience that is clearly related to the position.
- Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science
- A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university
- Experience in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g., Python) and skill in at least one mid-level language (e.g., C)), data mining, advanced statistical analysis (e.g., statistical foundations of machine learning, statistical approaches to missing data, time series), advanced mathematical foundations, artificial intelligence, workflow and reproducibility, data management and curation, data modeling and assessment (e.g., model selection, evaluation, and sensitivity analysis), experience as a data scientist working to support a single or multiple domain area, and/or software engineering.
Desired Qualifications:
- Working knowledge of Big Data, dataflows, and ML/AI familiarity
- Working knowledge of Jupyter notebooks
- Working knowledge of Spark
Responsibilities include, but are not limited to:
- Working knowledge of statistics, programing and predictive modeling
- Use programming languages (e.g., Python, R) to manipulate and analyze large data sets
- Design and implement machine learning, data science and advanced analytical algorithms
- Provide statistical analysis as well as (e.g. variability, sampling error, inference, hypothesis testing, EDA, applications of linear models), data management, data mining, data modeling and assessment
Benefits:
ANS offers excellent compensation along with a generous benefits package to include:
- Family Medical, Dental (w/ adult orthodontia) and Vision coverage
- Pet Discount Program
- PTO (Paid Time Off)
- Maternity/ Paternity Leave
- Supplemental Military Leave Pay
- 11 Paid Holidays
- 401(k) plan with 6% Company Contribution
- Generous Professional Development Program
- 100% Employer paid Short- and Long-Term Disability
- 100% Employer paid Life Insurance
- Supplemental Whole Life Insurance
- Lucrative Referral Bonus Program
- Annual Allowance for ANS Swag
- Potential for Paid Overtime
- Flexible Work Schedules
Applied Network Solutions, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age or protected veteran status and will not be discriminated against on the basis of disability.
*Disclaimer: Salary is an open band for Indeed purposes and may not accurately represent the salary band for this position*
