Data Scientist II – Machine Learning & AI

Employment Type: Long-Term Contract

Work Arrangement: 100% Remote

About the Opportunity

We are hiring a Data Scientist II on behalf of one of our established U.S.-based clients for a long-term remote contract opportunity .

This role sits within a data product workplace and is focused on designing, building, and deploying machine learning models and production-ready data products that support enterprise initiatives.

This is a hands-on, engineering-oriented Data Science position. The successful candidate will translate complex business problems into scalable, data-driven solutions and take models beyond experimentation into real production environments.

The ideal candidate has practical experience building and operationalizing machine learning models , strong Python and SQL skills, and experience working within contemporary cloud environments. Exposure to LLMs, Retrieval-Augmented Generation (RAG), NLP, and modern AI platforms is highly desirable.

Key Responsibilities

- Design, build, train, evaluate, and deploy machine learning models and data products for enterprise applications.
- Analyze complex datasets to identify opportunities for product, operational, and business improvements.
- Translate business and operational requirements into scalable data science and machine learning solutions.
- Perform feature engineering, data preparation, exploratory analysis, and model development.
- Develop models using techniques such as classification, regression, clustering, NLP, optimization, and neural networks.
- Build production-ready solutions rather than limiting work to exploratory analysis or reporting.
- Contribute to advanced AI initiatives involving LLMs, RAG, NLP, and hybrid modeling approaches .
- Develop and improve frameworks and tools for automated data collection and processing.
- Collaborate with software engineering teams to integrate models into production systems using APIs, pipelines, and cloud services.
- Support deployment and lifecycle management of models using platforms such as Azure Machine Learning,



AWS SageMaker, or comparable technologies .
- Contribute to the design of data products, including model outputs, APIs, and downstream integrations.
- Perform model validation, testing, monitoring, and documentation to ensure reliability and reproducibility.
- Develop and support A/B testing frameworks and methods for evaluating model quality.
- Participate in technical design discussions and contribute to architecture and implementation decisions.
- Work within established software development lifecycle (SDLC) practices, including version control, testing, code reviews, and release processes.
- Clearly communicate model behavior, assumptions, limitations, and results to both technical and non-technical stakeholders.
- Stay current with emerging AI, machine learning, and data science technologies.

Required Qualifications

- Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or another relevant technical discipline.
- Approximately 5+ years of professional experience in Data Science, Machine Learning, Applied AI, or a closely related field.
- Strong hands-on experience with Python .
- Strong working knowledge of SQL and relational data.
- Solid foundation in machine learning, statistical modeling, and applied data science.
- Demonstrated experience developing and deploying machine learning models into production environments .
- Practical understanding of feature engineering, model evaluation, validation, and experimentation.
- Experience with machine learning techniques such as classification, regression, clustering, decision trees, neural networks, NLP, and related approaches.
- Experience working with Azure, AWS,



or another major cloud platform .
- Familiarity with cloud-based ML platforms such as Azure Machine Learning, AWS SageMaker, or equivalent .
- Understanding of data pipelines, APIs, and production integration patterns.
- Experience working within structured software development environments and SDLC practices.
- Strong analytical and problem-solving abilities.
- Strong written and verbal communication skills.

Preferred Qualifications

- Master’s degree in a relevant technical discipline.
- Hands-on experience with Large Language Models (LLMs) .
- Experience developing Retrieval-Augmented Generation (RAG) solutions.
- Experience with Natural Language Processing (NLP).
- Exposure to Azure OpenAI, AWS Bedrock, or comparable AI platforms .
- Experience integrating ML or AI solutions into enterprise software products.
- Experience building APIs or working closely with software engineering teams on model deployment.
- Experience with MLOps, model monitoring, CI/CD, or automated ML deployment pipelines.

What We Are Looking For We are particularly interested in candidates who have taken machine learning solutions from development into real-world production environments .

This is not primarily a reporting, dashboarding, or purely analytical Data Scientist position. Candidates should be comfortable writing production-quality Python, working with engineering teams, deploying models, and taking ownership of technical solutions.

Experience with modern Generative AI technologies such as LLMs and RAG is valuable , but candidates should also have a strong foundation in traditional machine learning and statistical modeling.

Contract Details

- Long-term contract opportunity
- 100% remote
- Work with an established U.S.-based enterprise client
- Collaborate with experienced Data Science, Product, and Engineering teams
- Opportunity to work on production ML, AI, and enterprise data products
- Candidates must be based in Canada and legally able to work as an independent contractor in Canada .

📌 Data Scientist (Canada)
🏢 Hanalytica
📍 Canada