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Company: SAIC
Location: REMOTE WORK, VA
Career Level: Mid-Senior Level
Industries: Technology, Software, IT, Electronics

Description

Description

SAIC is seeking a highly experienced and results-driven Senior Data Scientist. The ideal candidate will have a strong technical foundation in data analytics, data modeling, machine learning, natural language processing, security, and artificial intelligence technologies in cloud native environments. This exceptional position will be a key member of an emerging technologies lab which will support many product teams as they seek to modernize, automate, and innovate their applications. This role requires deep technical expertise and the ability to design, develop, and engineer the innovation, automation, and modernization of complex projects that drive business value and strategic insights.

Key Responsibilities:

  • Operate and maintain an innovation lab for the ideation, design, and engineering of cloud native product modernization and innovation using emerging technologies.
  • Develop end-to-end plans for AI/ML/NLP innovations that are compliant with USPTO cybersecurity policies.
  • Develop pilots, prototypes, and proof of concept solutions to validate emerging technology, modernization, and innovation opportunities.
  • Implement transparency, traceability, and appropriate security handling in line with best practices and applicable compliance standards including Authorization To Operate certifications.
  • Collaborate with cross-functional teams including data engineering, product, and business stakeholders to translate requirements into data-driven solutions.
  • Support total experience initiatives including customer experience, user experience and human centered design through focus groups, metrics, wireframes, mockups, and information architecture development.
  • Design and implement predictive models, machine learning algorithms, and statistical analyses to solve complex business problems.
  • Conduct exploratory data analysis and generate actionable insights from large and complex datasets.
  • Develop data management and data governance plans
  • Develop reusable code libraries and best practices for modernization and innovation development and deployment.
  • Stay current with advancements in data science, machine learning, and AI research.
  • Mentor more junior data scientists and guide the team in adopting new technologies and techniques.
  • Support Agile product teams as an emerging technologies and data strategies subject matter expert.
  • Analyze data and usage to find patterns and solutions to business challenges.
  • Make low risk plans and present business recommendations and demonstrations to stakeholders in a clear manner based on data architecture best practices.

Qualifications

Required Qualifications:

  • Masters' degree or higher in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
  • Minimum 10 years of relevant experience in data science, analytics, machine learning, artificial intelligence or a similar role.
  • Candidates must be able to obtain and maintain a Public Trust clearance based on USPTO regulations
  • Candidates must have lived in the United States for the last 2 years
  • Proven track record of delivering impactful emerging technology value including AI/ML/NLP innovations and data-driven solutions in a cloud native environment.

Technology Stack & Skills:

  • Programming Languages: Python, R, SQL
  • AI, ML, NLP Frameworks, models, and tools
  • Machine Learning & Statistical Tools PyTorch
  • Data Manipulation & Analysis
  • Visualization Tools Tableau, Power BI
  • Big Data & Cloud Platforms: Hadoop, Hive, AWS (S3, SageMaker, Redshift), Azure, and GCP
  • Version Control & Collaboration: Git, Docker

Desired Qualifications:

  • Experience with MLOps, model monitoring, and deployment pipelines.
  • Familiarity with NLP, computer vision, or deep learning techniques.

Target salary range: $160,001 - $200,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.


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