Data Scientist Skill Level 2

TO BE CONSIDERED FOR THIS POSITION: YOU MUST CURRENTLY HAVE AN ACTIVE TS/SCI WITH POLYGRAPH SECURITY CLEARANCE WITH THE FEDERAL GOVERNMENT. (U.S. CITIZENSHIP REQUIRED).

• Polygraph clearance within 7 years.
• Programming
  
  Languages:
  
  Proficiency in Python and R.
• Statistical Analysis:
  Strong foundation in statistics and probability.
• Machine Learning:
  Knowledge of machine learning algorithms and frameworks such as Tensor Flow and Scikit-Learn.
• Data Wrangling:
  Ability to clean and organize complex datasets.
• Database Management:
  Familiarity with SQL and database management systems such as Postgre
  
  SQL and Mongo
  
  DB.
• Data Visualization:
  Skills in tools such as Tableau and Matplotlib.

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.

• Produce data visualizations that provide insight into dataset structure and meaning.
• Work with subject matter experts (SMEs) to identify important information in raw data and develop scripts that extract this information from a variety of data formats.
• 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 the 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.

We are committed to providing fair and competitive compensation. The salary range for our positions varies depending on accepted contractual position skill level. These salaries fall within the range of $78,000 to $275,000 per year. The exact salary will be determined based on the candidate's work location, specific role, skill set, and level of expertise.

• Health Coverage:
  Medical, dental, and vision insurance.
• Additional Insurance:
  Basic Life/AD&D, Voluntary Life/AD&D, Short and Long-Term Disability, Accident, Critical Illness, Hospitalization Indemnity, and Pet Insurance.
• Retirement Plan: 401(k) plan with company match.
• Paid Time Off:
  Generous PTO, paid holidays, parental leave, and more.
• Wellness:
  Access to wellness programs and mental health support.
• Professional Development:
  Opportunities for growth, including tuition reimbursement.

• Flexible work arrangements, including remote work options.
• Flexible Spending Accounts (FSAs).
• Employee referral programs.
• Bonus opportunities.
• Technology allowance.
• A diverse, inclusive, and supportive workplace culture.