Data Scientist Job at Leidos, College Park, MD

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  • Leidos
  • College Park, MD

Job Description

Job Description

Description

The NISC IV program at Leidos is seeking a Data Scientist to work closely with cross-functional teams to analyze large, complex datasets and develop data-driven solutions to critical business challenges. Your work will help shape strategic decisions, optimize operations, and optimize solutions that will directly support aviation safety for the Federal Aviation Administration (FAA).

Primary Responsibilities:

The successful candidate will be responsible for the design and development of methods, processes, and systems to consolidate and analyze structured and unstructured, diverse and/or large data sets from disparate sources. Application of mathematical, statistical, scientific, and/or computational techniques, such as probability models, machine learning, data mining, pattern recognition, data visualization, predictive analytics, data warehousing, artificial intelligence, and similar complex methods. The primary responsibilities of the position are:

  • Develop integration of data and workflows between operational safety activities, work tracking metrics and office oversight to gauge effectiveness, timeliness and performance of safety investigation operations
  • Collect, clean, and analyze structured and unstructured data from various sources.
  • Work closely with multidisciplinary teams to implement data solutions.
  • Uphold data governance principles and adhere to ethical practices for handling sensitive and confidential data.
  • Work closely with data analysts and investigative analysts to ensure accurate and reliable data sources.
  • Prepare formal written reports clearly stating the results of analysis ensuring accuracy and adequacy.
  • Effectively maintain relationships with internal and external stakeholders, including peers, staff, and management.
  • Collaborate with management and stakeholders to understand the mission needs and translate them into actionable initiatives.
  • Stay updated on industry best practices and emerging trends in data science and provide recommendations for continuous improvement.
  • Utilize various data collection and analysis tools and scripting languages to create and validate data sets used by analysts.

Basic Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related field and 8 to 12 years or relevant experience or Masters Degree and 6 years of relevant experience.
  • 2+ years of experience in a data science or analytics role.
  • Strong proficiency in Python or R, and SQL.
  • Experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, XGBoost).
  • Solid understanding of statistics, data modeling, and experimentation.
  • Excellent communication skills and ability to translate complex findings into actionable insights.
  • Excellent analytical and problem-solving skills
  • Optimistic attitude, poise, and team player.
  • Ability to obtain a Public Trust clearance.

Preferred Qualifications:

  • Experience working in [industry, e.g., fintech, healthcare, e-commerce].
  • Familiarity with cloud platforms such as AWS, GCP, or Azure.
  • Strong proficiency in Python or R, and SQL.
  • Experience supporting data modernization projects
Original Posting: May 30, 2025

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range: Pay Range $104,650.00 - $189,175.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

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