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.
Key Responsibilities
AI & Machine Learning
- 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.
Statistical Modeling & Analytics
- 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.
Computer Vision & OCR
- 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.
Stakeholder Engagement & Communication
- 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.
