3-5 years of experience in data science and machine learning
Strong proficiency in Python and SQL
Hands-on experience with MLOps and AI/ML development frameworks
Familiarity with Angular, Typescript, and related technologies
Knowledge of unit testing frameworks like Jest and Playwright
Responsibilities
Develop predictive machine learning models and recommender systems
Implement and monitor AI/ML lifecycle processes
Evaluate and deploy Generative AI solutions
Conduct A/B testing and feature engineering
Utilize modern frameworks such as TensorFlow and PyTorch for model development
Benefits
Flexible work locations in Burlington, MA; Durham, NC; or Irving, TX
Opportunity to work with cutting-edge AI/ML technologies
Collaborative and innovative work environment
Professional development opportunities in advanced data science techniques
Access to resources for continuous learning and skill enhancement
Full Job Description
Overview:
Job Title: Data Scientist
Location: Burlington, MA or Durham, NC or Irving, TX.
Primary Skills: Python, SQL, MLOps, and modern AI/ML development frameworks, AI/ML lifecycle, GenAI solutions including RAG, agentic AI workflows, LLM evaluation frameworks
Experience: 3 - 5 years
Job Description:
Experience with primary skills as Angular, Typescript, NgRx, RxJs, AI, ML, Python.
Hands on latest Angular version 16+ with Standalone components, Signals/change detection, Reactive Forms, PrimeNG, Angular Material, Ag-Grid and State Management.
Strong proficiency in Python, SQL, MLOps, and modern AI/ML development frameworks (Scikit-learn, TensorFlow, PyTorch, Hugging Face, AWS Sagemaker, etc.)
Knowledge of unit testing frameworks through Jest, Playwright.
Strong hands-on experience building predictive machine learning models, recommender systems, ranking models, and prescriptive optimization models
Expertise across the AI/ML lifecycle, including experimentation, A/B testing, feature engineering, model development, deployment, monitoring, measurement, and governance
Experience evaluating, deploying, and governing GenAI solutions, including RAG, knowledge retrieval, agentic AI workflows, LLM Finetuning, LLM evaluation frameworks.
