Data Scientist

Blue Orange Digital•New York, NY

2h•Remote

About The Position

Blue Orange Digital is a boutique data & AI consultancy that delivers enterprise-grade results. We design and build modern data platforms, analytics, and ML/AI Agent solutions for mid‑market and enterprise clients across Private Equity, Financial Services, Healthcare, and Retail. Our teams work with technologies like Databricks, Snowflake, dbt, and the broader Microsoft ecosystem to turn messy, real-world data into trustworthy, actionable insight. We’re a builder‑led, client‑first culture that prizes ownership, clear communication, and shipping high‑impact work. Note: Please submit your resume in English, as all application materials must be in English for review and consideration. Position Overview: Blue Orange is seeking an experienced Machine Learning Engineer to drive our machine-learning and LLM Engineering initiatives. The ideal candidate possesses a deep passion for AI tech, is proficient in Python and SQL, and has a proven ability to deliver high-impact ML/AI and data science projects from ideation to production. Engagement Type: Staff Augmentation Type: Contractor / Independent Contractor (1099 only) Location: Fully remote; candidates must be based in the United States, Canada, or Mexico

Requirements

Bachelor's degree or higher in Computer Science or a related field.
5+ years of industry experience as a hands-on practitioner in ML/AI, Data Science, or Data Engineering.
Proven track record of successful delivery of ML/AI and data projects.
Experience with NLP and LLM-based technologies and frameworks.
Proficiency in programming languages such as Python and SQL and familiarity with the Databricks platform where some of the modeling takes place (JavaScript a plus).
Understanding and passion for Test Driven Design.
Familiarity with ETL/ELT concepts and best practices.
Expertise in 2–3 major cloud and data platforms (e.g., AWS, GCP, Azure, Snowflake, or Databricks).
Effective communication skills and the ability to collaborate effectively with both technical and non-technical stakeholders.
Independent enough to push the thinking and critically review analysis/identify next steps while working in close collaboration with our consultants.

Nice To Haves

Experience with prompt engineering and RAG techniques a plus.
Experience with Docker a plus.

Responsibilities

Collaborate with cross-functional teams to understand business requirements and design to productionize machine learning, ML ops, traditional AI, LLMs, and agentic AI solutions into practical product-driven applications.
Design and implement application integrations to leverage newly built machine learning, ML ops, traditional AI, LLMs, and agentic AI products.
Build solutions that improve the delivery speed and scalability of product pipelines.
Leverage managed and serverless cloud offerings to create performant and scalable cloud-native application solutions and data pipelines.
Design and implement advanced machine learning models, including predictive analytics, elasticity modeling, and large dataset analytics, using techniques like regression, classification, Bayesian methods, and Retrieval-Augmented Generation (RAG).
Develop and deploy Agentic AI prototypes and other advanced machine learning solutions.
Work closely with GenAI engineers to integrate prompt engineering and RAG components into production systems.
Participate in customer engagement activities, clearly communicating technical concepts and project progress to stakeholders.