SITE is a trailblazer in asset management and data analytics. Our dynamic team of experts’ crafts top-tier technology solutions, leveraging advanced imagery to deliver proactive, predictive, and actionable data. We empower our clients to extend the lifespan of their properties while saving time and money with our cutting-edge, insightful analytics and technology.

We are seeking a versatile Data Scientist with a strong background in Operations Research

(OR) and machine learning to join our innovative team. The ideal candidate will develop

decision science algorithms for our SaaS product while also applying broader data science and

machine learning techniques to drive insights and enhance our product's capabilities.

Primary Responsibilities:

-Design and implement decision science algorithms and machine learning models for

integration into our SaaS product

-Apply Operations Research techniques to create innovative solutions for complex

decision-making processes

-Develop and maintain machine learning pipelines for various data science tasks (e.g.,

classification, regression, clustering)

-Conduct exploratory data analysis and feature engineering to improve model

performance

-Collaborate with product managers and software engineers to translate algorithms and

models into product features

-Perform statistical analyses and create data visualizations to communicate insights to

stakeholders

-Stay current with advancements in OR, machine learning, and data science,

incorporating new techniques into our product

-Contribute to the technical vision and roadmap of our product's analytical capabilities

Required Skills and Experience:

-Master's degree or  PhD in Operations Research, Data Science, Computer Science, or a

related quantitative field

-Experience applying OR and machine learning techniques in a professional setting

-Strong programming skills in Python and SQL

-Expertise in algorithm design, optimization techniques, and machine learning model

development

-Proficiency with data science and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch)

-Solid understanding of statistical analysis and experimental design

-Professional experience with version control systems (e.g., Git) and collaborative

software development practices

-Excellent problem-solving and analytical skills

-Strong communication abilities to explain complex concepts to both technical and

non-technical audiences

Preferred Qualifications:

-Experience developing algorithms and models for commercial software products,

particularly in a SaaS environment

-Knowledge of MLOps practices and tools for deploying and maintaining models in

production

-Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP)

-Familiarity with computer vision techniques and their applications