Data Science, AI, Statistical Modeling

Description

SAIC is seeking Data Scientist with deep expertise in AI/ML, advanced statistical modeling, and computer vision/OCR to design, develop, and deploy data-driven solutions that support mission-critical objectives. The ideal candidate combines strong quantitative skills with hands-on engineering experience, and can translate complex business or mission needs into scalable analytical and AI solutions.

You will work closely with subject-matter experts to understand requirements and translate those requirements into technical solutions to .to build models that extract value from structured and unstructured data, including images, documents, and text. Additionally, the models must detect changes from a defined baseline and incorporate the results into customer required report formats.

• Design, build, and validate machine learning models (supervised, unsupervised, and semi-supervised) for prediction, classification, clustering, and change detection..
• Develop and maintain end-to-end ML pipelines, including data preparation, feature engineering, model training, evaluation, and deployment.
• Apply deep learning techniques (e.g., CNNs, RNNs/LSTMs/Transformers) where appropriate to solve complex business or mission problems

• Develop and apply statistical models (e.g., regression, generalized linear models, hierarchical/multilevel models, time series, survival analysis, experimental design) to support forecasting, risk assessment, and operational decision-making
• Perform rigorous exploratory data analysis (EDA) and statistical inference to identify patterns, trends, drivers, and causal relationships
• Design and analyze A/B tests or other experiments to measure the impact of products, policies, or processes
• Communicate uncertainty, assumptions, and limitations of models using appropriate statistical methods

• Develop computer vision and OCR solutions for image and document understanding, including detection, classification, segmentation, and feature extraction
• Implement document layout and entity extraction models (e.g., for forms, reports, scanned documents, PDFs) to convert unstructured visual content into structured data
• Fine-tune or customize pre-trained vision and OCR models to specific domains, languages, and document types

• Partner with business, program, or mission owners to understand requirements, define measurable objectives, and translate them into analytical solutions
• Present results and recommendations to technical and non-technical stakeholders through clear reports, visualizations, and briefings
• Document methodologies, models, and processes for transparency, reproducibility, and knowledge transfer

• Active TS/SCI with Poly clearance
• Must be a US Citizen
• Bachelors and five (5) years or more experience;
  Masters and three (3) years or more experience;
  PhD and 0 years related experience
• 3–5+ years
  (or equivalent hands‑on experience) in data science, machine learning, or applied statistics
• Strong proficiency in
  Python
  (preferred) orR, including use of standard data science libraries
• Demonstrated experience building and deploying machine learning and statistical models on real‑world datasets
• Solid foundation in statistics and probability, including:
  • Hypothesis testing, confidence intervals, power analysis
  • Regression modeling (linear, logistic, regularization methods)
  • Time series or forecasting techniques
• Hands‑on experience with
  deep learning frameworks such as
  Tensor Flow
  ,
  Keras
  , or
  Py Torch
• Proven experience in
  computer vision
  , including at least some of:
  • Image classification, object detection, or segmentation
  • Use of CNN‑based architectures (e.g., Res…